Search Results for "so" - Page 19
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Showing 1303 open source projects for "so"
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PyTorch Lightning
The lightweight PyTorch wrapper for high-performance AI research
...PyTorch Lightning can easily be applied for any use case. With just a quick refactor you can run your code on any hardware, run distributed training, perform logging, metrics, visualization and so much more! -
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Wagtail
A Django content management system focused on flexibility & UX
...Built on Django, Wagtail offers precise control and flexibility for designers, developers and editors. Designed by developers for developers, Wagtail plays nicely with everything else in your tech stack so you can do more and focus on perfecting your site. Designers will find Wagtail’s simple templating system ideal for building beautiful websites just the way they want, without any CMS constraints. Editors can create beautiful, modular streams of content that they can create once and publish everywhere. Simply put, it’s the CMS that makes everyone happy! -
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PyScaffold
Python project template generator with batteries included
...After cd-ing into your new project and creating (or activating) an isolated development environment (with virtualenv, conda or your preferred tool), you can do the usual editable install. All configuration can be done in setup.cfg like changing the description, URL, classifiers, installation requirements and so on as defined by setuptools. That means in most cases it is not necessary to tamper with setup.py. -
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Aden Hive
Outcome driven agent development framework that evolves
...Once deployed, agents can capture failure data, evolve automatically to meet their success criteria, and redeploy without constant manual intervention, delivering continual improvement over time. The framework also includes human-in-the-loop nodes, credential management, cost and budget controls, and real-time observability so teams can monitor execution and intervene as needed. Hive is designed for production environments and supports a wide range of large language models, local models, and business system connectivity. -
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5
UNO
A Universal Customization Method for Single and Multi Conditioning
...Because the project is new (see activity logs for 2025), it seems to aim at bridging between single-subject customization and multi-subject generation in generative modeling — potentially useful for personalized content creation, flexible composition, or controlled generation tasks. UNO likely offers tools to fine-tune or condition generation models so that they can incorporate novel subjects, enabling users to produce custom outputs beyond standard training distribution. -
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InfiniteYou
Flexible Photo Recrafting While Preserving Your Identity
...Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via residual connections — so that the output matches the person’s identity closely, without sacrificing visual quality or text-image alignment. The team uses a multi-stage training strategy with synthetic multi-sample data per identity to fine-tune for both identity consistency and aesthetic quality. Compared to prior methods, InfiniteYou significantly improves on identity similarity, text-prompt adherence, overall image quality, and avoids common problems such as face copy-pasting artifacts. -
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Open Vision Agents by Stream
Build Vision Agents quickly with any model or video provider
...It focuses on combining video understanding models, such as YOLO and Roboflow based detectors, with real time large language models like OpenAI Realtime and Gemini Live to create interactive experiences. The framework uses Stream’s ultra low latency edge network so agents can join sessions quickly and maintain very low audio and video latency while processing frames and generating responses. Developers work with an agent abstraction that connects video edge providers, LLMs, and processors into pipelines, making it easier to orchestrate tasks like object detection, pose estimation, and conversational guidance. ... -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
...NeMo 2.0 introduces a Python-based configuration system, replacing YAML with more flexible, programmable configs that can be versioned and composed for different experiments. The framework builds on PyTorch Lightning–style modular abstractions, so training scripts are composed from reusable components for data loading, models, optimizers, and schedulers, which simplifies experimentation and adaptation. NeMo is designed to scale: with tools like NeMo-Run, users can orchestrate large-scale experiments across thousands of GPUs. -
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Dia
A TTS model capable of generating ultra-realistic dialogue
...It can also produce nonverbal vocalizations like laughter, coughs, clearing the throat, and similar sounds, which are crucial for making synthetic conversations feel human. Dia is released with pretrained checkpoints and inference code, with weights hosted on Hugging Face, so researchers and developers can quickly try it or integrate it into pipelines. The base model currently targets English and has around 1.6 billion parameters, offering a strong balance between realism and computational cost, while the ecosystem also includes Dia2. -
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shot-scraper
A command-line utility for taking automated screenshots of websites
...Under the hood it uses a modern browser (installed via a one-time shot-scraper install step) and exposes options for viewport size, full-page versus clipped screenshots, and device emulation. Beyond simple captures, it can run custom JavaScript before taking the shot, allowing you to open menus, scroll, or manipulate the DOM so the screenshot reflects the desired state. The project is deeply integrated with automation workflows: examples show it running in scheduled jobs, GitHub Actions, and bots that publish screenshots to social media or use them in docs. It ships with detailed documentation, a tutorial, and a template repository that lets you spin up an automated screenshot pipeline. -
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Code-Mode
Plug-and-play library to enable agents to call MCP and UTCP tools
Code-Mode is a plug-and-play library that lets AI agents call tools by executing TypeScript (or via a Python wrapper) instead of making many individual function calls. Its core philosophy is that language models are very good at writing code, so rather than exposing hundreds of separate tool endpoints, you give the model a single “code execution” tool that has access to your full toolkit through code. 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. ... -
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Agent Stack
Deploy and share agents with open infrastructure
...It also offers multi-model, multi-provider support (OpenAI, Anthropic, Gemini, IBM WatsonX, Ollama etc.), letting users compare performance and cost across models. For developers and organizations building AI-agent products or automations, Agent Stack gives a scaffold that handles the “plumbing”, so they can focus on logic and domain. -
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MetricFlow
MetricFlow allows you to define, build, and maintain metrics in code
MetricFlow is an open-source semantic layer engine designed to help organizations define, manage, and query business metrics in a consistent, governed way. It works alongside a data stack—typically built with dbt—and allows you to express metrics as YAML‐based definitions tied to semantic models and dimension tables, rather than embedding logic ad-hoc across many dashboards or scripts. When a user or tool requests a metric (e.g., “monthly revenue by region”), MetricFlow generates optimized,... -
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web-eval-agent MCP Server
An MCP server that autonomously evaluates web applications
...It’s positioned as a “let the coding agent debug itself” companion: the agent launches the app, navigates flows, captures evidence, and iterates on failures without manual copy-pasting of logs. 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. ... -
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Otter-Grader
A Python and R autograding solution
Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an... -
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authentik
The authentication glue you need
...It can be seamlessly integrated into existing environments to support new protocols. authentik is also a great solution for implementing sign-up, recovery, and other similar features in your application, saving you the hassle of dealing with them. authentik is an open-source Identity Provider focused on flexibility and versatility. You can use authentik in an existing environment to add support for new protocols, implement sign-up/recovery/etc. in your application so you don't have to deal with it, and many other things. You can adopt authentik to your environment, regardless of your requirements. Need an Active-Directory integrated SSO Provider? Do you want to implement a custom enrollment process for your customers? Are you developing an application and don't want to deal with User verification and recovery? ... -
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ipwb
A distributed and persistent archive replay system using IPFS
...IPFS is a peer-to-peer content-addressable file system that inherently allows deduplication and facilitates opt-in replication. ipwb splits the header and payload of WARC response records before disseminating into IPFS to leverage the deduplication, builds a CDXJ index with references to the IPFS hashes returned, and combines the header and payload from IPFS at the time of replay. An important aspect of archival replay systems is rewriting various resource references for proper memento reconstruction so that they are dereferenced properly from the archive from around the same datetime as of the root memento and not from the live site (in which case the resource might have changed or gone missing). Many archival replay systems perform server-side rewriting, but it has its limitations when URIs are generated using JavaScript. -
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UForm
Multi-Modal Neural Networks for Semantic Search, based on Mid-Fusion
...This type of models is well-suited for retrieval in large collections. The most famous example of such models is CLIP by OpenAI. Early-fusion models encode both modalities jointly so they can take into account fine-grained features. Usually, these models are used for re-ranking relatively small retrieval results. Mid-fusion models are the golden midpoint between the previous two types. Mid-fusion models consist of two parts – unimodal and multimodal. -
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git-delete-merged-branches
Command-line tool to delete merged Git branches
...Deletion is a sharp knife that requires care. While git reflog would have your back in most cases, git-delete-merged-branches takes safety seriously. git push is used with --force-with-lease so if the server and you have a different understanding of that branch, it is not deleted. There is no use of os.system or shell code to go wrong. -
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Zappa - Serverless Python
Serverless Python
...If the queue of incoming requests grows too large, some requests will time out. With Zappa, each request is given its own virtual HTTP "server" by Amazon API Gateway. AWS handles the horizontal scaling automatically, so no requests ever time out. Each request then calls your application from a memory cache in AWS Lambda and returns the response via Python's WSGI interface. After your app returns, the "server" dies. -
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Imagen - Pytorch
Implementation of Imagen, Google's Text-to-Image Neural Network
...It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior network is needed after all. And so research continues. For simpler training, you can directly supply text strings instead of precomputing text encodings. (Although for scaling purposes, you will definitely want to precompute the textual embeddings + mask) -
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Albumentations
Fast image augmentation library and an easy-to-use wrapper
...Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations supports different computer vision tasks such as classification, semantic segmentation, instance segmentation, object detection, and pose estimation. ... -
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Jina
Build cross-modal and multimodal applications on the cloud
...Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via Jina Hub. Fast deployment to Kubernetes, Docker Compose and Jina Cloud. Improved engineering efficiency thanks to the Jina AI ecosystem, so you can focus on innovating with the data applications you build. -
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Vidi2
Large Multimodal Models for Video Understanding and Editing
...Vidi targets applications like intelligent video editing, automated video search, content analysis, and editing assistance, enabling users to efficiently locate relevant segments and objects in hours-long footage. The system is built with open-source release in mind, giving developers access to model code, inference scripts, and evaluation pipelines so they can reproduce research results or integrate Vidi into their own video-processing workflows. -
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VideoChat
Real-time voice interactive digital human
...It is built as a Gradio Python demo, exposing a web interface where users can talk to an animated avatar that lip-syncs to synthesized speech while responding intelligently. The system is customizable: you can define your own avatar appearance and voice, and it supports voice cloning so you can generate a new voice from a short 3–10 second reference sample. The tech stack integrates FunASR for speech recognition, Qwen for language understanding, multiple TTS engines like GPT-SoVITS, CosyVoice, or edge-tts, and MuseTalk for talking-head generation.
