Search Results for "setup-subversion" - Page 6
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Showing 292 open source projects for "setup-subversion"
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AI Shell
CLI tool turning natural language into executable shell commands
...It integrates into a developer’s existing workflow by running directly in the terminal and responding to prompts with suggested commands. Users can configure it with an API key and begin issuing requests immediately, making setup relatively straightforward. -
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fast-stable-diffusion
Fast-stable-diffusion + DreamBooth
fast-stable-diffusion is a community-curated GitHub repository that provides Colab notebooks and integration examples for running Stable Diffusion and associated UIs like AUTOMATIC1111, ComfyUI, and DreamBooth directly on Google Colab environments. Rather than being a standalone packaged application, this project offers ready-to-use interactive notebooks that install and launch full-feature Stable Diffusion web UIs inside Colab without requiring complex local setups or GPU installations.... -
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MCP Language Server
mcp-language-server gives MCP enabled clients access semantic tools
...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. The project maintains active issues and PRs, indicating ongoing polish around multi-language routing and robustness. ... -
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LiteMultiAgent
The Library for LLM-based multi-agent applications
LiteMultiAgent is a lightweight and extensible multi-agent reinforcement learning (MARL) platform designed for rapid experimentation. It allows researchers to design and test coordination, competition, and collaboration scenarios in simulated environments. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Image Extender
Seamlessly extend any image in any direction with AI
...Beyond outpainting, it provides workspaces for parallax backgrounds, autotile sets, animated sprite sheets, and transparent prop sprites. It is useful for creators who need fast visual expansion, game-ready assets, or browser-based AI art workflows without a large local setup. -
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Smart Excalidraw
A smart, powerful, and beautiful excalidraw drawing tool
Smart Excalidraw Next is an AI-powered diagramming tool that allows users to generate professional-quality visual diagrams directly from natural language descriptions, combining generative AI with the flexibility of the Excalidraw canvas. It leverages large language models to interpret user input and automatically produce structured diagrams such as flowcharts, architecture diagrams, ER diagrams, and mind maps with logical layouts and clean visual organization. One of its key innovations is... -
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Karpathy
An agentic Machine Learning Engineer
karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. The system is tightly integrated with... -
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JiT
PyTorch implementation of JiT
...Rather than predicting noise, JiT models directly predict clean image data, which the research suggests aligns better with the manifold structure of natural images and leads to stronger generative performance at high resolution. This implementation supports training on large datasets like ImageNet with configurable model variants, and practical scripts for setup, training, and evaluation on GPUs are included, leveraging PyTorch’s ecosystem for real-world experimentation. The repository’s layout contains modular engine, model, and training scripts enabling researchers and engineers to customize components such as training regimes, noise schedules, and evaluation routines. -
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Self-Hosted AI Starter Kit
Template that quickly sets up a local AI environment
...It’s targeted at both technical and semi-technical users, allowing you to build custom AI workflows, chat experiences, or intelligent automation systems by integrating modular services that communicate via APIs; the setup is intended to be both repeatable and scalable for varied use cases. -
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Weaviate
Weaviate is a cloud-native, modular, real-time vector search engine
Weaviate in a nutshell: Weaviate is a vector search engine and vector database. Weaviate uses machine learning to vectorize and store data, and to find answers to natural language queries. With Weaviate you can also bring your custom ML models to production scale. Weaviate in detail: Weaviate is a low-latency vector search engine with out-of-the-box support for different media types (text, images, etc.). It offers Semantic Search, Question-Answer-Extraction, Classification, Customizable... -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. 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... -
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DeepSeek-V3.2-Exp
An experimental version of DeepSeek model
...The key innovation in this version is DeepSeek Sparse Attention (DSA), a sparse attention mechanism that aims to optimize training and inference efficiency in long-context settings without degrading output quality. According to the authors, they aligned the training setup of V3.2-Exp with V3.1-Terminus so that benchmark results remain largely comparable, even though the internal attention mechanism changes. In public evaluations across a variety of reasoning, code, and question-answering benchmarks (e.g. MMLU, LiveCodeBench, AIME, Codeforces, etc.), V3.2-Exp shows performance very close to or in some cases matching that of V3.1-Terminus. ... -
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KnowNote
A local-first AI knowledge base & NotebookLM alternative
...It lets users build an intelligent, searchable knowledge base from uploaded documents such as PDFs, Word files, PowerPoints, and web pages, and then interact with that content using LLM-powered chat, summarization, and reasoning tools. Unlike many NotebookLM alternatives that rely on Docker or cloud deployments, KnowNote runs natively on desktop platforms without complex setup, meaning all data stays local unless the user opts to integrate with self-managed or private LLM APIs. Its retrieval-augmented generation (RAG) system offers semantic search and traceable source references, and it supports multiple LLM providers through a flexible plugin-style provider architecture. -
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CodexPro
Use ChatGPT Developer Mode as a local coding agent for your repo
...It starts a local server for the current workspace so ChatGPT can read files, search code, apply scoped edits, run guarded shell checks, and review changes. The project is designed around local control rather than hosting code or proxying model access through a third-party service. It supports setup, start, doctor, settings, handoff, and pro modes for different levels of agent involvement. Public access can be routed through options such as Cloudflare tunnels, ngrok, Tailscale Funnel, or local-only mode. CodexPro is useful for developers who want ChatGPT to act like a repo-aware coding assistant while keeping the actual workspace on their own machine. -
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HiDream-I1
Open-source image generative foundation model
...It supports direct Python inference scripts, an interactive Gradio demo, and integration through the Hugging Face Diffusers library. The model uses a Llama 3.1 text encoder path and requires the proper Hugging Face access setup for automatic downloads. It is useful for researchers, developers, and creative AI builders who want an open text-to-image model with strong benchmark performance and multiple deployment options. -
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AnyTool
AnyTool: Universal Tool-Use Layer for AI Agents
AnyTool is an open-source universal tool-use layer for AI agents that addresses the critical problem of how autonomous agents reliably interact with external tools and environments. Rather than having each agent handle tool invocation logic on its own, AnyTool provides a standardized interface and orchestrator that intelligently selects and manages tools, reduces context overhead, and improves execution reliability across diverse capabilities like web APIs, local commands, and GUI... -
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Moltworker
Run OpenClaw on Cloudflare Workers
...Acting as a middleware Worker and script adaptor, moltworker packages the OpenClaw agent and its dependencies into a Cloudflare Sandbox container that can operate at scale on the global edge network, offering an always-on deployment without users needing their own servers. With this setup, developers can host and interact with a personal AI assistant that maintains persistent conversations, integrates with chat platforms, and provides a control UI protected by Cloudflare Access. The project includes web UIs, Cloudflare configuration files, and scripts to authenticate devices, manage environment secrets, and enable optional services like persistent R2 storage for chat history. -
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Agent Payments Protocol (AP2)
Building a Secure and Interoperable Future for AI-Driven Payments
AP2 is a project released by Google’s “Agentic Commerce” initiative, focusing on a protocol and reference implementation for agent-driven or AI-mediated payments. In effect, AP2 aims to define a secure, interoperable protocol that allows software agents to act on behalf of users—making payments or shopping decisions autonomously—while preserving necessary security, auditability, and trust. The repository contains sample scenarios (in Python, Android, etc.) that illustrate how agents,... -
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GLM-4-Voice
GLM-4-Voice | End-to-End Chinese-English Conversational Model
...GLM-4-Voice builds upon the bilingual strengths of the GLM architecture, supporting both Chinese and English, and is designed to handle long-form conversations with context retention. The repository provides model weights, inference demos, and setup instructions for deploying speech-enabled AI systems. -
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DeepSeek Coder
DeepSeek Coder: Let the Code Write Itself
...Multiple sizes of the model are offered (e.g. 1B, 5.7B, 6.7B, 33B) so users can trade off inference cost vs capability. The repo provides model weights, documentation on training setup, evaluation results on common benchmarks (HumanEval, MultiPL-E, APPS, etc.), and inference tools. -
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butterbase
Open-source backend-as-a-service
...The platform is designed to connect with AI coding tools through MCP, allowing agents to provision and manage backend infrastructure while developers build the frontend. It is especially useful for founders, builders, and “vibe coders” who want to move quickly without spending time on DevOps or backend setup. Butterbase also emphasizes open building blocks and reduced lock-in through a Postgres-backed architecture. Its main value is giving AI-assisted development workflows a ready backend that agents can operate directly. -
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Kimi-Audio
Audio foundation model excelling in audio understanding
...Instead of fragmenting work across specialized models, Kimi-Audio handles automatic speech recognition (ASR), audio question answering, automatic audio captioning, speech emotion recognition, and audio-to-text chat in one system, enabling developers to build rich, multimodal audio applications without stitching together disparate components. It uses a novel model setup that combines continuous acoustic features with discrete semantic tokens to richly capture sound and meaning across speech, music, and environmental audio. -
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Cofounder
AI tool that generates full-stack web apps with generative UI systems
...Developers can describe a project and allow the system to incrementally produce a working codebase that includes both backend services and a modern web frontend built with a Vite and React setup. Cofounder also provides a dashboard and local API environment that helps manage project generation, iteration, and interaction with the system. Generated projects are stored locally and can be launched using standard development commands, allowing developers to run and modify the code that the system produces. Cofounder relies on configurable nodes and sequences that define how AI operations are executed. -
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CoAI.Dev
Next Generation AI One-Stop Internationalization Solution
...It is designed to support a wide range of LLM and image-generation backends (including OpenAI-compatible endpoints), while also providing an admin dashboard for user, subscription, and pricing controls, so it can be operated as a self-hosted AI product rather than just a personal playground. The app emphasizes cross-device conversation sync and sharing without requiring extra services like WebDAV, aiming to reduce setup friction for end users and increase retention for operators. It also includes advanced content rendering, with strong Markdown support for tables, code highlighting, LaTeX, and diagram-style outputs, so conversations can function like rich technical documents. -
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Gpt-Agreement-Payment
End-to-end protocol replay toolkit for ChatGPT Plus/Team/Pro sub
Gpt-Agreement-Payment is a research-oriented automation toolkit focused on subscription payment flows, protocol replay behavior, and anti-fraud mechanism analysis. It documents and implements controlled workflows around account setup, payment routing, runtime state storage, and operational monitoring. The project includes both command-line and web UI modes, with Docker and manual deployment options. It stores runtime output and logs in a local SQLite-backed structure for review and debugging. Because it touches payment systems, account workflows, and fraud controls, it should be treated strictly as a research and compliance-sensitive project, not as a general-purpose automation product. ...