Search Results for "project" - Page 5
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Showing 1832 open source projects for "project"
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HY-World 1.5
A Systematic Framework for Interactive World Modeling
HY-WorldPlay is a Hunyuan AI project focusing on immersive multimodal content generation and interaction within virtual worlds or simulated environments. It aims to empower AI agents with the capability to both understand and generate multimedia content — including text, audio, image, and potentially 3D or game-world elements — enabling lifelike dialogue, environmental interpretations, and responsive world behavior. -
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Next AI Draw.io
A next.js web application that integrates AI capabilities with draw.io
Next AI Draw.io is an AI-enhanced diagramming application that integrates generative intelligence into the familiar draw.io-style visual workflow. The project aims to help users create diagrams, flowcharts, and structured visual content more efficiently by leveraging AI-assisted generation and editing capabilities. It combines modern web technologies with diagram automation features to reduce the manual effort typically required in visual design tools. The system is intended for developers, product teams, and technical planners who need rapid diagram creation within collaborative environments. ... -
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grepai
Semantic Search & Call Graphs for AI Agents
grepai is a privacy-first, semantic code search CLI designed to replace traditional keyword-based search with meaning-aware queries, letting developers and code tools find relevant code by what it does rather than just text matches. It builds a semantic index of a project using vector embeddings, enabling natural language queries like “authentication logic” to return contextually relevant functions and modules even when naming differs dramatically, making code exploration far more intuitive. In addition to semantic search, grepai offers call graph tracing so developers can understand which functions call or are called by others, aiding impact analysis and confident refactoring. ... -
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Vibe
Transcribe on your own
Vibe is an open-source project by thewh1teagle designed to deliver a collaborative and interactive social application experience, though its specifics depend on its evolving community scope; its development often focuses on connecting users through dynamic features that can include chat, shared spaces, and immersive interactions. The repository typically includes backend logic, frontend integration, and real-time communication stacks to support live user engagement, performance optimizations, and modular features that adapt to social workflows. ... -
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Wurst Client
Minecraft Wurst Hacked Client v7
Wurst7 is an open-source modified Minecraft client that includes a large collection of gameplay modifications commonly referred to as “hacks” or cheat modules. The project provides a custom client environment where players can enable various automated tools, overlays, and gameplay enhancements that alter how the game behaves. These features may include movement enhancements, automation utilities, and visualization tools that provide additional information about the game world. Wurst7 is typically installed as a Fabric mod and runs alongside the standard Minecraft Java Edition client. ... -
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MuseGAN
An AI for Music Generation
...This representation allows the neural network to capture rhythmic patterns, harmonic relationships, and structural dependencies across instruments. The architecture is based on convolutional GAN models that learn temporal musical structure and inter-track relationships from training data. The project was trained using the Lakh Pianoroll Dataset, a large collection of multitrack musical sequences derived from MIDI files. -
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Gemini-API
Reverse-engineered Python API for Google Gemini web app
...This enables developers to incorporate Gemini into Python applications, scripts, bots, or tools without relying solely on official SDKs. The wrapper supports streaming responses, model selection, and handling of the web-based authentication/session mechanisms used by Google’s interface. While the project offers a powerful integration, users should note that the API is reverse-engineered (not officially supported by Google) and may face changes or rate-limits. The project is licensed under AGPL-3.0, emphasizing the “open” nature but also requiring derivative works to remain open. It has a strong community following and active discussions/issue tracking around model support, error handling, and new features. -
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MetaGPT
The Multi-Agent Framework
...MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. -
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Godot MCP
MCP server for interfacing with Godot game engine
...The tool is particularly valuable for AI-assisted game development, as it creates a feedback loop where agents can execute code, observe results, and iteratively improve their outputs. It also includes advanced features for manipulating scenes, managing assets, and editing project structures, making it possible to automate large portions of the development process. By exposing Godot functionality through a standardized MCP interface, it ensures compatibility with various AI clients such as Claude Code or Cursor. -
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python-small-examples
Focus on creating classic Python small examples and cases
...The examples are intentionally short and easy to read, making them useful for beginners who want to understand Python syntax and programming logic step by step. The repository is organized as a large collection of small scripts and notes that can be browsed individually without needing to study a full project. -
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OpenSandbox
OpenSandbox is a general-purpose sandbox platform for AI applications
...OpenSandbox is particularly useful for AI agents, code execution services, and any scenario where untrusted code must be executed safely. Its architecture emphasizes flexibility, security boundaries, and operational consistency across environments. Overall, the project aims to standardize sandbox execution for modern AI and cloud native workflows. -
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stable-diffusion.cpp
Diffusion model(SD,Flux,Wan,Qwen Image,Z-Image,...) inference
...It enables text-to-image and image-to-image generation, supports a growing set of models like SD1.x, SD2.x, SDXL, SD-Turbo, Qwen Image, and more, and is continually updated with support for cutting-edge model variants including video and image editing models. The project is built on the ggml backend, which allows efficient execution on CPUs and GPUs via backends like CUDA, Vulkan, Metal, OpenCL, and SYCL, making it suitable for everything from desktops to mobile devices. It includes options for ControlNet, LoRA models, upscaling via ESRGAN, and advanced sampling techniques, giving developers and users a rich toolkit for creative workflows. -
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FlashAttention
Fast and memory-efficient exact attention
...It achieves this by using IO-aware algorithms that minimize memory reads and writes, reducing the quadratic memory overhead typically associated with attention operations. The project provides implementations of FlashAttention, FlashAttention-2, and newer iterations optimized for modern GPU architectures such as NVIDIA Hopper and AMD accelerators. By improving both forward and backward pass efficiency, it enables training and inference of large language models with longer sequence lengths and higher throughput. ... -
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tiny-llm
A course of learning LLM inference serving on Apple Silicon
tiny-llm is an educational open-source project designed to teach system engineers how large language model inference and serving systems work by building them from scratch. The project is structured as a guided course that walks developers through the process of implementing the core components required to run a modern language model, including attention mechanisms, token generation, and optimization techniques. -
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Qwen3.5
Qwen3.5 is the large language model series developed by Qwen team
Qwen3.5 is part of Alibaba’s Qwen family of large language and multimodal foundation models, designed to power advanced AI applications such as chatbots, coding assistants, and autonomous agents. The project represents a significant step toward “agentic AI,” meaning models that can reason through multi-step tasks and interact with external tools or environments rather than only generating text. Qwen3.5 builds on earlier Qwen generations by improving multilingual understanding, reasoning ability, and efficiency, while also introducing native multimodal capabilities that allow the model to work with both language and visual inputs. ... -
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Open ChatGPT Atlas
Open Source and Free Alternative to ChatGPT Atlas
...Unlike a fixed chat app, Atlas is designed as a foundation that can be extended with plugins, external APIs, and custom logic to support domain-specific assistants, agent-like behaviors, and multi-task workflows. The project includes utilities for session management to preserve context across interactions, structured interfaces for streaming responses, and integration layers that let you plug in third-party tools and services. It often forms the basis for research, prototyping, or production systems where the default ChatGPT interface isn’t flexible enough. -
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WhisperJAV
Uses Qwen3-ASR, local LLM, Whisper, TEN-VAD
WhisperJAV is an open-source speech transcription pipeline designed specifically for generating subtitles for Japanese adult video content. The project addresses challenges that standard speech recognition models face when transcribing this type of audio, which often includes low signal-to-noise ratios and large numbers of non-verbal vocalizations. Traditional automatic speech recognition systems can misinterpret these sounds as words, leading to inaccurate transcripts. WhisperJAV introduces a specialized pipeline that separates text generation from timestamp alignment, allowing the system to generate transcripts and then align them with audio using forced alignment techniques. ... -
18
SD.Next
All-in-one WebUI for AI generative image and video creation
...It is designed as a power-user environment where model management, generation features, and workflow controls are centralized in a single UI rather than spread across separate scripts and utilities. The project emphasizes broad model support and includes mechanisms for discovering, downloading, and configuring models through integrated tooling, lowering the setup burden for experimentation. It also provides documentation and an ecosystem of guides that help users move from basic generation to more advanced usage patterns, including API-based automation. ... -
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The Minimalist Entrepreneur
Claude Code skills based on The Minimalist Entrepreneur
...It acts as a modular layer that can be integrated into AI agents to improve how they perform tasks such as reasoning, coding, communication, and decision-making. The project emphasizes composability, allowing individual skills to be combined into larger workflows that solve more complex problems. It is designed to be human-readable and easy to extend, making it accessible for developers who want to customize or build their own AI skill sets. The repository reflects a broader shift toward treating AI behavior as programmable and modular rather than monolithic. ... -
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Style-Bert-VITS2
Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles
...For those who only need synthesis, the project is published as a Python library (pip install style-bert-vits2) and can run on CPU without an NVIDIA GPU, though training still requires GPU hardware. -
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Flower
Flower: A Friendly Federated Learning Framework
...Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state-of-the-art systems. Different machine learning frameworks have different strengths. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
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MCP Claude Code
MCP implementation of Claude Code capabilities and more
The MCP Claude Code server implements Claude Code-like functionality, allowing AI assistants to directly execute instructions for modifying and improving project files. It leverages the Model Context Protocol for seamless integration with various MCP clients. -
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Better Agents
Standards for building agents, better
...The system generates structured project files, including configuration documents that define the architecture, roles, and capabilities of the agent system. By following these conventions, developers can ensure that their agents adhere to widely accepted design patterns and operational standards. -
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self-llm
Tutorial tailored for Chinese babies on rapid fine-tuning
...The project also includes guides for integrating models into real applications, including command-line interfaces, web demos, and frameworks like LangChain. By combining theory, configuration instructions, and runnable examples, self-llm lowers the barrier to entry for students and engineers who want to experiment with open-source models. -
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SoniTranslate
Synchronized Translation for Videos
...Under the hood, it uses advanced speech and diarization models to separate speakers, align audio with timecodes and respect subtitle timing, which lets the generated dub track stay in sync with the original video structure. The project supports a wide range of languages for translation, spanning major world languages (English, Spanish, French, German, Chinese, Arabic, etc.) and many regional or less widely spoken languages, making it suitable for broad internationalization. It offers multiple usage modes, including a Colab notebook for cloud-based experimentation, a Hugging Face Space demo for quick trials, and instructions.
