Search Results for "without code" - Page 4
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Showing 182 open source projects for "without code"
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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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Outplacement, Executive Coaching and Career Development | CareermindsBy helping to avoid the potential risks of RIFs or layoffs through our global outplacement services, companies can move forward with their goals while preserving their internal culture, employer brand, and bottom lines.
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AgenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills
AgenticSeek is a fully local autonomous AI assistant designed as a privacy-focused alternative to cloud-based agent platforms. It runs entirely on the user’s hardware and can autonomously browse the web, write code, and plan multi-step tasks without sending data to external services. The system is optimized for local reasoning models and emphasizes zero cloud dependency to maintain full user control. AgenticSeek includes intelligent agent selection, allowing it to determine the best internal agent to handle a given request. It also supports hands-free workflows such as automated web form interaction and information extraction. ... -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
...It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter counts without linear inference cost explosion. The model is intended to be competitive with closed-source image generation systems, aiming for high fidelity, prompt adherence, fine detail, and even “world knowledge” reasoning (i.e. leveraging context, semantics, or common sense in generation). The GitHub repo includes code, scripts, model loading instructions, inference utilities, prompt handling, and integration with standard ML tooling (e.g. ... -
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AI Runner
Offline inference engine for art, real-time voice conversations
...It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a mode-based architecture with specialized “modes” such as Author, Code, Research, QA and General, and a workflow manager that automatically routes user requests to the right agent based on the task. The project has a strong focus on developer ergonomics, with thorough development guidelines, environment configuration using .env variables, and a clear structure for tests, tools and agents. -
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OmniBox
Collect, organize, use, and share, all in OmniBox
...Inspired by the omnibox concept used in modern browsers, the system combines search functionality with command execution so that users can access information and perform tasks without navigating complex menus. The mirrored distribution on SourceForge exists to provide an additional download source and preserve access to the software’s source code independent of its original repository. Tools like Omnibox typically emphasize extensibility, allowing developers to add plugins or integrations that connect the interface to other systems such as APIs, search engines, or automation tools. -
viewneo - Smart software for digital advertising boardsviewneo is a user-friendly, cloud-based solution that allows companies of all sizes to set up digital signage
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OpenAI Agent Skills
Skills Catalog for Codex
...It organizes reusable, task-specific workflows, instructions, scripts, and resources into modular skill folders so that an AI agent can reliably perform complex tasks without repeated custom prompting, making agent behavior more predictable and composable. Each skill is defined with clear metadata and instructions organizing how an AI assistant should complete specific tasks ranging from project management to code generation and documentation assistance. The repository supports community contributions, allowing developers to add new skills or update existing ones to keep the catalog relevant and practical for evolving use cases. -
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Aden Hive
Outcome driven agent development framework that evolves
Hive is an open-source agent development framework that helps developers build autonomous, reliable, self-improving AI agents by letting them describe goals in ordinary natural language instead of hand-coding detailed workflows. Rather than manually defining execution graphs, Hive’s coding agent generates the agent graph, connection code, and test cases based on your high-level objectives, enabling outcome-driven agent creation that fits real business processes. 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. ... -
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mergekit
Tools for merging pretrained large language models
...It also provides configuration-driven workflows that allow users to experiment with different merging strategies without modifying source code. -
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vJEPA-2
PyTorch code and models for VJEPA2 self-supervised learning from video
VJEPA2 is a next-generation self-supervised learning framework for video that extends the “predict in representation space” idea from i-JEPA to the temporal domain. Instead of reconstructing pixels, it predicts the missing high-level embeddings of masked space-time regions using a context encoder and a slowly updated target encoder. This objective encourages the model to learn semantics, motion, and long-range structure without the shortcuts that pixel-level losses can invite. The... -
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AWS Neuron
Powering Amazon custom machine learning chips
...Using Neuron developers can easily train their machine learning models on any popular framework such as TensorFlow, PyTorch, and MXNet, and run it optimally on Amazon EC2 Inf1 instances. You can continue to use the same ML frameworks you use today and migrate your software onto Inf1 instances with minimal code changes and without tie-in to vendor-specific solutions. Neuron is pre-integrated into popular machine learning frameworks like TensorFlow, MXNet and Pytorch to provide a seamless training-to-inference workflow. It includes a compiler, runtime driver, as well as debug and profiling utilities with a TensorBoard plugin for visualization. -
Cloud-hosted construction project information management for improved communication, and increased efficiency.Newforma empowers over 4M professionals and 1,500 AECO firms worldwide by revolutionizing Project Information Management. We transform vast amounts of project data into a meticulously organized, easily accessible, and fully searchable resource—all from a single, centralized platform. From pre-construction to years after completion, Newforma ensures you have the critical information you need at every stage of your projects.
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AudioCraft
Audiocraft is a library for audio processing and generation
...The repo provides inference scripts, checkpoints, and simple Python APIs so you can generate clips from prompts or incorporate the models into applications. It also contains training code and recipes, so researchers can fine-tune on custom data or explore new objectives without building infrastructure from scratch. Example notebooks, CLI tools, and audio utilities help with prompt design, conditioning on reference audio, and post-processing to produce ready-to-share outputs. -
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Code2Prompt
Convert codebases into structured prompts optimized for LLM analysis
code2prompt is an open source command line tool designed to convert an entire codebase into a structured prompt that can be easily used with large language models. It analyzes a project directory, gathers relevant source files, and formats them into a single prompt that includes the source tree and code content. This approach helps developers quickly provide full project context to AI models without manually copying files or assembling prompts. code2prompt is built in Rust and focuses on performance, enabling fast traversal of large repositories while maintaining low resource usage. It also respects common project conventions such as .gitignore, ensuring that unnecessary files are automatically excluded from the generated prompt. ... -
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Lagent
A lightweight framework for building LLM-based agents
...Instead of using LLMs only for text generation, Lagent enables developers to transform models into agents capable of performing actions such as retrieving data, executing code, or interacting with APIs. The system includes modular components that allow developers to connect different models and tools within the same agent architecture. Its design emphasizes simplicity and flexibility so that developers can experiment with different agent workflows without needing a complex infrastructure setup. Lagent can also be deployed as a web service to support distributed or multi-agent applications. -
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AutoViz
Automatically Visualize any dataset, any size
AutoViz is a Python data visualization library designed to automate exploratory data analysis by generating multiple visualizations with minimal code. The primary goal of the project is to help data scientists and analysts quickly understand patterns, relationships, and anomalies within datasets without manually writing complex plotting code. With a single command, the library can automatically generate dozens of charts and graphs that reveal insights into the structure and quality of the data. ... -
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Agentless
An agentless approach to automatically solve software development
Agentless is an open-source framework that applies large language models to automatically resolve software development issues without relying on complex autonomous agent systems. The project proposes an alternative approach to AI-driven code repair that avoids the overhead of multi-agent orchestration by using a structured pipeline for identifying and fixing bugs. When solving a problem, the system first performs localization to determine which files, functions, or code segments are most likely responsible for the issue. ... -
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Agent Lightning
The absolute trainer to light up AI agents
...The project emphasizes minimalist integration, so you can drop this into existing systems without extensive rewrites, focusing instead on iterative performance improvement. -
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JEPA
PyTorch code and models for V-JEPA self-supervised learning from video
JEPA (Joint-Embedding Predictive Architecture) captures the idea of predicting missing high-level representations rather than reconstructing pixels, aiming for robust, scalable self-supervised learning. A context encoder ingests visible regions and predicts target embeddings for masked regions produced by a separate target encoder, avoiding low-level reconstruction losses that can overfit to texture. This makes learning focus on semantics and structure, yielding features that transfer well... -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
...It supports iterative experimentation, allowing developers to rapidly improve agents without rebuilding systems from scratch. PySpur also enables deployment of finalized workflows after testing, making it suitable for both development and production use. Overall, it acts as an integrated environment for designing, evaluating, and managing AI-driven processes. -
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python-small-examples
Focus on creating classic Python small examples and cases
python-small-examples is an open-source educational repository that contains hundreds of concise Python programming examples designed to illustrate practical coding techniques. The project focuses on teaching programming concepts through small, focused scripts that demonstrate common tasks in data processing, visualization, and general programming. Each example highlights a specific function or programming pattern so that learners can quickly understand how to apply Python features in... -
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DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
...The project includes support for multiple draft models, example integration code, and scripts to benchmark performance, and it is structured to work with popular model serving stacks like SGLang and the Hugging Face Transformers ecosystem. -
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Composio
Composio equip's your AI agents & LLMs
Empower your AI agents with Composio - a platform for managing and integrating tools with LLMs & AI agents using Function Calling. Equip your agent with high-quality tools & integrations without worrying about authentication, accuracy, and reliability in a single line of code. -
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
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Red Discord Bot
A multi-function Discord bot
...You can turn Red into an admin bot, music bot, trivia bot, new best friend or all of these together! CustomCommands allows you to create simple commands for your bot without requiring you to code your own cog for Red. If the command you attempt to create shares a name with an already loaded command, you cannot overwrite it with this cog. Installation is easy, and you do not need to know anything about coding! Aside from installing and updating, every part of the bot can be controlled from within Discord. ... -
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Index
The SOTA Open-Source Browser Agent
...Index can perform tasks such as navigating pages, filling forms, collecting data, and analyzing web content without requiring manual scripting for each website. -
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LLMs-from-scratch
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters... -
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geo-seo-claude
GEO-first SEO skill for Claude Code
geo-seo-claude is an AI-powered tool designed to automate the creation of geographically optimized SEO content using large language models, helping businesses improve their visibility in local search results. It leverages AI to generate location-specific content tailored to different regions, allowing users to scale SEO efforts across multiple cities or markets without manual content creation. The system focuses on producing structured and keyword-optimized pages that align with search...
