Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 30
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Showing 1619 open source projects for "git:/git.code.sf.net/p/docfetcher/code"
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Inventory and Order Management Software for Multichannel SellersWe are the most powerful inventory and order management platform for Amazon, Walmart, and multichannel product sellers. Centralize orders, product information, and fulfillment operations to run more efficiently, sell more products, and stay compliant with marketplace requirements so you can grow profitably.
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Run applications fast and securely in a fully managed environmentRun frontend and backend services, batch jobs, deploy websites and applications, and queue processing workloads without the need to manage infrastructure.
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1
Python Programming Hub
Learn Python and Machine Learning from scratch
...The project contains a wide range of tutorials and exercises that cover Python fundamentals, programming concepts, and applied techniques for data analysis and machine learning. Many sections are implemented as Jupyter notebooks, allowing learners to run code interactively while reading explanations of the concepts involved. The repository emphasizes hands-on learning by demonstrating real programming tasks such as data manipulation, statistical analysis, visualization, and automation. It also includes examples of commonly used libraries such as NumPy, Pandas, and other tools used in data science workflows. -
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Plano
Delivery infrastructure for agentic apps
Plano is an AI-native proxy and data plane designed to simplify the infrastructure required to deploy and operate agentic applications in production environments. It removes repetitive plumbing work from application code by centralizing capabilities such as agent routing, orchestration, guardrails, observability, and model selection. Built on modern proxy technology and compatible with any language or AI framework, Plano enables developers to focus on core agent logic instead of infrastructure complexity. The system provides intelligent LLM routing APIs that support model agility, along with filter chains for safety, moderation, and memory hooks. ... -
3
Computer Vision in Action
A computer vision closed-loop learning platform
...It serves as a hands-on companion for learners and engineers who want to understand not just the theory, but how computer vision is actually implemented for tasks like object detection, image classification, feature tracking, optical flow, and image segmentation. The repository includes structured code examples, scripts, and notebooks that cover pipeline construction, preprocessing, model inference, and visual output rendering, making it easy for newcomers or intermediate practitioners to adapt patterns to their own projects. It also explores how to combine classical computer vision techniques with modern neural network-based models, offering insight into when each approach is most effective. -
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Model Zoo
Please do not feed the models
FluxML Model Zoo is a collection of demonstration models built with the Flux machine learning library in Julia. The repository provides ready-to-run implementations across multiple domains, including computer vision, natural language processing, and reinforcement learning. Each model is organized into its own project folder with pinned package versions, ensuring reproducibility and stability. The examples serve both as educational tools for learning Flux and as practical starting points for... -
Outbound sales softwareAdversus is an outbound dialing solution that helps you streamline your call strategies, automate manual processes, and provide valuable insights to improve your outbound workflows and efficiency.
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5
TensorFlow Serving
Serving system for machine learning models
TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. It deals with the inference aspect of machine learning, taking models after training and managing their lifetimes, providing clients with versioned access via a high-performance, reference-counted lookup table. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data. The... -
6
The Operator Splitting QP Solver
The Operator Splitting QP Solver
...The algorithm is absolutely division-free after the setup and it requires no assumptions on problem data (the problem only needs to be convex). It just works. OSQP has an easy interface to generate customized embeddable C code with no memory manager required. OSQP supports many interfaces including C/C++, Fortran, Matlab, Python, R, Julia, Rust. -
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wa-automate-nodejs
WhatsApp tool for chatbots with advanced features
...For more details see Easy API. After executing create() function, @open-wa/wa-automate will create an instance of WA web. If you are not logged in, it will print a QR code in the terminal. Scan it with your phone and you are ready to go! @open-wa/wa-automate will remember the session so there is no need to authenticate every time. -
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Oh My OpenCode Slim
Slimmed, cleaned and fine-tuned oh-my-opencode fork
Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents,... -
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markstream-vue
A Vue 3 renderer specifically built for AI-powered streaming Markdown
...The framework focuses on eliminating jitter and reflow issues that commonly occur when rendering progressively generated text, ensuring a smooth and readable user experience even during rapid updates. It integrates advanced rendering support for complex content types such as code editors via Monaco, diagrams via Mermaid, and mathematical expressions via KaTeX, all optimized for incremental updates. The architecture is tailored for reactive front-end environments, leveraging Vue’s reactivity system to efficiently update only the necessary parts of the DOM. -
The AI workplace management platformBy combining AI workflows, predictive intelligence, and automated insights, OfficeSpace gives leaders a complete view of how their spaces are used and how people work. Facilities, IT, HR, and Real Estate teams use OfficeSpace to optimize space utilization, enhance employee experience, and reduce portfolio costs with precision.
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10
Search with Lepton
Lightweight demo to build a conversational AI search engine quickly
...It retrieves information from supported search engines and uses that context to generate responses through a retrieval-augmented generation approach. The implementation is intentionally minimal, containing fewer than 500 lines of code while still providing a complete working example of an AI-powered search system. It includes both a backend service written in Python and a web interface that allows users to interact with the search engine in a conversational format. Developers can configure different search providers and language models through environment variables, making it flexible for experimentation and prototyping. -
11
LLM Agents Papers
Must-read Papers on LLM Agents
...The project organizes academic literature that explores how language models can act as agents capable of reasoning, planning, and interacting with external tools or environments. Rather than providing software code, the repository functions as a structured knowledge base that helps researchers navigate the rapidly expanding field of agent-based AI research. Papers are categorized into thematic groups covering topics such as tool use, planning algorithms, reasoning strategies, and multi-agent collaboration. The repository helps readers understand how agent architectures are evolving and how they are applied in domains such as robotics, software automation, and decision-making systems. ... -
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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
...Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment, and long-horizon reinforcement learning to build intrinsic optimization capability rather than relying on simple post-hoc tuning. The system operates in a ReAct-style loop where the agent profiles baseline implementations, writes CUDA code, compiles it in a sandbox, and iteratively refines performance. CUDA-Agent has demonstrated strong benchmark results, achieving high pass rates and significant speedups compared with compiler baselines such as torch.compile. -
13
Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
...Each skill is a self-contained folder with structured metadata and guidance that tells an agent how to execute tasks such as dataset creation, model training, evaluation, or Hub operations. The project is designed to be interoperable across major agent ecosystems, including Claude Code, OpenAI Codex, Gemini CLI, and Cursor, making it a cross-platform building block for agent automation. By formalizing best practices and workflows, Skills helps transform general-purpose coding agents into domain-aware assistants that can execute complex ML pipelines with less manual prompting. The repository also includes ready-to-use skills for common Hugging Face operations and encourages teams to extend them with custom domain logic. -
14
FireRedTTS-2
Long-form streaming TTS system for multi-speaker dialogue generation
FireRedTTS2 is a next-generation open-source text-to-speech (TTS) system focused on long-form, streaming speech synthesis for multi-speaker dialogue, delivering stable natural speech with context-aware prosody and reliable speaker transitions that support real-time and conversational applications. It features a specialized streaming speech tokenizer and a dual-transformer architecture that enables low latency and high-quality synthesis, making it suitable for interactive systems like... -
15
Playwriter
Chrome extension to let agents control your browser
Playwriter is an open-source project that combines a Chrome extension with a CLI to allow autonomous agents to control a web browser directly using Playwright code in a stateful sandbox environment. The system enables browser automation by running Playwright commands through a persistent session managed by a background extension, allowing agents or scripts to navigate, interact with, and query browser contexts without losing state between commands. This makes it valuable for scenarios where AI agents need to perform complex web automation tasks—like multi-step navigation, form interaction, or content extraction—without reinitializing context or state every time. ... -
16
GetProfile
User profile and long-term memory for your AI agent
...It then extracts structured traits and “memories” from those conversations, stores them, and injects the most relevant profile context back into future prompts so responses stay consistent and personalised over time. The goal is to make “memory” and user understanding an infrastructure concern rather than an app-by-app feature, so teams can add continuity with minimal code changes. Because it behaves like an OpenAI-compatible gateway, it can work with multiple providers and tools that already speak that API shape. -
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llm.c
LLM training in simple, raw C/CUDA
llm.c is a minimalist, systems-level implementation of a small transformer-based language model in C that prioritizes clarity and educational value. By stripping away heavy frameworks, it exposes the core math and memory flows of embeddings, attention, and feed-forward layers. The code illustrates how to wire forward passes, losses, and simple training or inference loops with direct control over arrays and buffers. Its compact design makes it easy to trace execution, profile hotspots, and understand the cost of each operation. Portability is a goal: it aims to compile with common toolchains and run on modest hardware for small experiments. ... -
18
Mosec
A high-performance ML model serving framework, offers dynamic batching
Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. -
19
ArrayFire
ArrayFire, a general purpose GPU library
...The community of ArrayFire developers invites you to build with us if you're interested and able to write top performing tensor functions. Together we can fulfill The ArrayFire Mission under an excellent Code of Conduct that promotes a respectful and friendly building experience. Rigorous benchmarks and tests ensuring top performance and numerical accuracy. Cross-platform compatibility with support for CUDA, OpenCL, and native CPU on Windows, Mac, and Linux. Built-in visualization functions through Forge. -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
We are working on new way for visual programming. We developed a desktop application called MLJAR Studio. It is a notebook-based development environment with interactive code recipes and a managed Python environment. All running locally on your machine. We are waiting for your feedback. The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. It is designed to save time for a data scientist. It abstracts the common way to preprocess the data, construct the machine learning models, and perform hyper-parameter tuning to find the best model. ... -
21
DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
...While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications of image tagging, object detection, segmentation, OCR, Audio, Video, Text classification, CSV for tabular data and time series. Neural network templates for the most effective architectures for GPU, CPU, and Embedded devices. Training in a few hours and with small data thanks to 25+ pre-trained models. ... -
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Datasets
Hub of ready-to-use datasets for ML models
Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep integration with the Hugging Face Hub, allowing you to easily load and share a dataset with the wider NLP community. ... -
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Llama Cookbook
Solve end to end problems using Llama model family
The Llama Cookbook is the official Meta LLaMA guide for inference, fine‑tuning, RAG, and multi-step use-cases. It offers recipes, code samples, and integration examples across provider platforms (WhatsApp, SQL, long context workflows), enabling developers to quickly harness LLaMA models -
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Simple MCP
A simple TypeScript library for creating MCP servers
simple-mcp is a TypeScript library designed to facilitate the creation of Model Context Protocol (MCP) servers. It offers a straightforward API, enabling developers to set up MCP servers with minimal code. The library emphasizes type safety through full TypeScript integration and incorporates parameter validation using Zod. It fully implements the MCP, ensuring compatibility with MCP clients. -
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embedchain
Framework to easily create LLM powered bots over any dataset
Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds.
