Search Results for "readme"
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Showing 43 open source projects for "readme"
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agents.md
A simple, open format for guiding coding agents
openai/agents.md is a repository whose primary file is AGENTS.md, a proposed open, lightweight convention (i.e. Markdown file) for guiding coding agents in software repositories. The idea is that AGENTS.md acts as a “README for agents”: a predictable, structured place where humans can put instructions, conventions, build/test commands, environment setup, and other guidance that generative agents (e.g. code-writing, code-assisting tools) should consult when operating in the repo. Instead of putting everything in README or doc files (which are more human-oriented and might mix high-level narrative), AGENTS.md is intended to surface agent-relevant details that help them “do the right thing” (tests, style, project structure, tooling). -
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WeChatMsg
Project aimed at extracting, exporting, and analyzing chat records
...Beyond simple export, the project includes mechanisms for analyzing chat histories and generating annual reports or visual summaries about messaging trends, interaction patterns, and more. The original README communicates a guiding philosophy about owning personal data and using it responsibly to train personalized AI agents or preserve memories. Although the repository has seen periods of inactivity and may not receive frequent updates, its widespread use indicates community interest in preserving chat logs and understanding conversation data outside of the WeChat interface. -
3
Agent Learning Hub
A curated AI Agent learning roadmap
Agent Learning Hub is a curated learning roadmap and resource collection for understanding AI agents. It is maintained as a central README-style knowledge hub rather than a software runtime or framework. The project organizes high-quality articles, official blogs, papers, open-source projects, engineering experience, and learning paths into a sequence that users can follow. It is especially useful for beginners and intermediate learners who want a structured entry point into the fast-moving agent ecosystem. ... -
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OhMyOpenCode
The Batteries-Included Agent that codes like you
OhMyOpenCode is an open-source starter kit and community ecosystem designed to help developers discover, contribute to, and manage open-source projects with greater ease and structure. It provides templates, organizational guidelines, and tooling that standardize how projects are set up — including recommended README structures, contribution workflows, issue templates, and automated CI/CD integrations — so maintainers can focus on building features instead of boilerplate. The repository also serves as a showcase and aggregation hub for quality open-source work, offering curated lists of notable projects, learning pathways, and contribution opportunities for developers at various skill levels. ... -
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OpenAI Realtime Embedded
Instructions on how to use the Realtime API on Microcontrollers
...The repo includes pointers to an ESP32 implementation (maintained as esp32 branch) and documentation that Espressif offers an official example in openai_demo. It does not appear to include a full cross-platform embedded SDK in the main branch (the core content is mostly links and minimal README), but acts as a launching point for integrating realtime on microcontrollers. -
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MCPHub
A unified hub for centralized management and dynamic organization
MCPHub is a unified hub that organizes many MCP servers behind clean Streamable HTTP (SSE) endpoints so clients can connect to “all tools,” a specific server, or logical groups. It’s designed to simplify multi-server operations: one process can multiplex several named STDIO servers and re-expose them over HTTP for IDEs and services. The README ships in multiple languages and includes deployment and routing guidance, signaling an intention to reach a broad user base. The project publishes to npm with frequent updates and provides a dashboard preview to help visualize connected servers. Community write-ups describe practical setups, including Docker images and hosted landing pages. ... -
7
Lemonade
Lemonade helps users run local LLMs with the highest performance
...The project positions itself as a “local LLM server” you can run on laptops and workstations, abstracting away backend differences while giving you a single place to serve and manage models. Its README emphasizes real-world adoption across startups, research groups, and large companies, signaling a focus on practical deployments rather than toy demos. The repository highlights easy onboarding with downloads, docs, and a Discord for support, suggesting an active user community. Messaging centers on squeezing maximum throughput/latency from modern accelerators without users having to hand-tune kernels or flags. ... -
8
Generative AI
Sample code and notebooks for Generative AI on Google Cloud
...It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and production-ready usage. The repository architecture is organised into folders like gemini/, search/, vision/, audio/, and rag-grounding/, which helps developers locate use cases by modality. It is licensed under Apache-2.0, opensourced and maintained by Google, meaning it's designed with enterprise-grade practices in mind. ... -
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JobWinner
Curated directory of thousands of generative AI tools by category
AI Collection is a curated repository that aggregates a large number of generative AI applications into a single organized directory. It serves as a discovery platform where users can browse and explore AI tools across a wide range of categories and use cases. Instead of providing software code for a single application, AI Collection acts as a structured index that lists AI tools along with brief descriptions and visual previews. It organizes thousands of AI applications into dozens of... -
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GitDiagram
AI tool that converts GitHub repositories into interactive diagrams
GitDiagram is an open source web application designed to help developers quickly understand the structure and architecture of GitHub repositories by automatically generating interactive diagrams. It analyzes repository metadata such as the file tree and project documentation to build a visual representation of how different components of a project relate to one another. It uses an AI-powered pipeline to interpret repository structure and transform that information into system design diagrams... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
...Many simple Python implementations can be found on Github, but none of them is able to beat a reasonable baseline on games such as Othello or Connect Four. As an illustration, the benchmark in the README of the most popular of them only features a random baseline, along with a greedy baseline that does not appear to be significantly stronger. -
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Stable Diffusion Version 2
High-Resolution Image Synthesis with Latent Diffusion Models
...The project sits within a larger ecosystem of Stability AI repositories (including inference-only reference implementations like SD3.5 and web UI projects) and the README points users toward compatible components, recommended CUDA/PyTorch versions. -
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Open Infra Index
Production-tested AI infrastructure tools
...Instead of a single monolithic codebase, it functions more like an index or launching point: linking and documenting a set of library repos (e.g. FlashMLA, DeepEP, DeepGEMM, 3FS, etc.) that together form DeepSeek’s infrastructure stack. The repo's README describes the project as sharing “humble building blocks” of their online service—code that is documented, deployed, and battle-tested in production. The timing of its opening matches DeepSeek’s “Open-Source Week” campaign (starting around February 2025) when they gradually released internal infrastructure components publicly. It is licensed under CC0-1.0 (Creative Commons Zero) to maximize openness. -
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CVPR 2025
Collection of CVPR 2025 papers and open source projects
...The list frequently highlights benchmarks, leaderboards, or notable results so readers can assess impact at a glance. Because conference content evolves rapidly, the repository is updated as authors release code or refine readme instructions, keeping the collection timely. For teams planning literature reviews, study groups, or rapid prototyping sprints, it acts as a central index to the year’s most relevant methods with working implementations. -
15
LitterBox
A secure sandbox environment for malware developers and red teamers
...It provides an isolated environment to exercise payloads against modern detection stacks, verify signatures and heuristics, and observe runtime characteristics without leaking binaries to third-party vendors. The README frames typical use cases: testing evasion, validating detections, analyzing behavior, and keeping sensitive tooling in-house. Repo metadata and author pages highlight an active security-tools ecosystem around the maintainer, with CI and pull-request activity suggesting ongoing development. The project positions itself as a safe proving ground to reduce surprises in the field while minimizing operational risk. ... -
16
Codex-5.5-codex-instruct-5.5
Prompt-injection utility aimed at modifying how Codex CLI behaves
...It claims to use an official configuration mechanism rather than binary modification, network interception, or process tampering. The project includes a Python script, an examples folder, assets, a README, and an MIT license. Its documentation also points users toward a newer visual project with desktop UI, provider switching, session management, and packaged installers. Because the stated purpose is to bypass safety restrictions, it should be treated as unsafe prompt-bypass research material rather than a normal developer productivity tool. -
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The Web MCP
A powerful Model Context Protocol (MCP) server
Bright Data’s Web MCP server gives AI assistants robust, real-time web capabilities through an MCP interface designed to avoid blocks, rate limits, and CAPTCHAs. It presents search, crawl, navigate, and extraction tools that agents can call directly, replacing brittle scraping prompts with typed operations. The README markets it as a “gateway” to the live web so assistants don’t fall back to stale training data. Bright Data also advertises a getting-started tier with a free monthly allotment, plus options for remote or self-hosted operation depending on governance needs. Ecosystem materials and examples show how it plugs into MCP-capable runtimes and agent frameworks. ... -
18
CutLER
Code release for Cut and Learn for Unsupervised Object Detection
...The codebase provides training and inference scripts, model configs, and references to benchmarking results that report large gains over prior unsupervised baselines. It’s intended for researchers exploring self-supervised and unsupervised recognition, offering a practical path to scale beyond costly labeled corpora. The README links papers and gives a high-level overview of components and expected outputs, with pointers to demos and assets. The repository is actively starred and structured as a typical research release with license, contribution guidelines, and security policy. -
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Diplomacy Cicero
Code for Cicero, an AI agent that plays the game of Diplomacy
...The repository includes training code, model checkpoints, and infrastructure for both language modelling (via the ParlAI framework) and reinforcement learning for strategy agents. It supports two variants: Cicero (which handles full “press” negotiation) and Diplodocus (a variant focused on no-press diplomacy) as described in the README. The codebase is implemented primarily in Python with performance-critical components in C++ (via pybind11 bindings) and is configured to run in a high‐GPU cluster environment. Configuration is managed via protobuf files to define tasks such as self-play, benchmark agent comparisons, and RL training. The project is now archived and read-only, reflecting that it is no longer actively developed but remains publicly available for research use. -
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Khazix Skills
Digital Life Kazik Open Source AI Skills Collection
Khazix Skills project is an automation framework designed to transform GitHub repositories into structured, reusable AI agent skills. It acts as a pipeline that analyzes a repository’s metadata, extracts relevant information such as README content and commit hashes, and converts it into a standardized skill format that can be integrated into agent ecosystems. The system emphasizes lifecycle management by embedding versioning, traceability, and metadata directly into generated skill files, allowing future updates and synchronization with the original repository. It also generates wrapper scripts that enable AI agents to interact with the underlying repository functionality without requiring deep manual integration. ... -
21
Profile Data
Analyze computation-communication overlap in V3/R1
...The idea is to bring transparency to internal efficiency tradeoffs, enabling researchers to reproduce, analyze, or improve on DeepSeek’s parallelism strategies. The README explains how trace data corresponds to forward/backward chunks, settings (e.g. EP64, TP1, 4K sequence length), and notes that pipeline communication is excluded for simplicity. -
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Gemini Next Chat
Deploy your private Gemini application for free with one click
...It’s licensed under MIT and has an active community of contributors; documentation and release notes note support for newer features like mixed image+text generation. The README warns of security configurations and customizing environment variables for model access. -
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MCP Language Server
mcp-language-server gives MCP enabled clients access semantic tools
mcp-language-server gives MCP-enabled clients semantic code-navigation powers—go-to-definition, find references, rename, and diagnostics—by brokering requests to language servers. It is not “a language server for MCP,” but an MCP server that exposes language-server–style capabilities to agents and chat IDEs through typed tools. The README demonstrates a streamlined setup: install the Go server, plug in one or more language servers per language, and the MCP client gains editor-grade navigation across the workspace. This helps agents reason precisely about symbols and files instead of guessing via grep-like prompts, enabling safer edits and better refactoring proposals. ... -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
...This approach can dramatically reduce the number of tool-call iterations needed in complex workflows, turning multi-step call chains into a single code execution with internal branching and loops. The repository contains both TypeScript and Python libraries, plus a code-mode-mcp component for integrating with MCP and UTCP ecosystems. Benchmarks in the README highlight improvements in latency and token cost for scenarios involving multiple tools, showing that code execution often outperforms traditional JSON-based function calling. -
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web-eval-agent MCP Server
An MCP server that autonomously evaluates web applications
...The repository focuses on developer ergonomics, exposing typed MCP tools so clients like Claude Desktop can start sessions, gather traces, and reason over failures with structured artifacts. Marketing and README material emphasize supercharging local debugging loops by combining live browser execution with LLM-driven hypotheses and fixes. Activity on the repo shows steady iteration, with issues and PRs centered on reliability and developer experience. In short, it wraps autonomous, in-editor web testing and diagnosis behind a predictable MCP interface.
