Search Results for "git:/git.code.sf.net/p/docfetcher/code" - Page 11
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721 projects for "git:/git.code.sf.net/p/docfetcher/code" with 2 filters applied:
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SoftCo: Enterprise Invoice and P2P Automation SoftwareSoftCo Accounts Payable Automation processes all PO and non-PO supplier invoices electronically from capture and matching through to invoice approval and query management. SoftCoAP delivers unparalleled touchless automation by embedding AI across matching, coding, routing, and exception handling to minimize the number of supplier invoices requiring manual intervention. The result is 89% processing savings, supported by a context-aware AI Assistant that helps users understand exceptions, answer questions, and take the right action faster.
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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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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LlamaDeploy
Deploy your agentic worfklows to production
...The project provides an asynchronous architecture that allows developers to deploy complex multi-agent workflows as scalable microservices. It enables teams to move from experimental prototypes to production systems with minimal changes to existing LlamaIndex code, making it easier to operationalize AI agents. The system supports orchestrating multiple services, handling communication between agents, and managing workflow execution in distributed environments. Developers can define workflows that involve multiple steps such as data retrieval, reasoning, tool invocation, and response generation, then deploy them using the framework’s infrastructure tools. ... -
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Anthropic SDK TypeScript
Access to Anthropic's safety-first language model APIs
anthropic-sdk-typescript is the TypeScript / JavaScript client library for the Anthropic REST API, enabling backend or Node.js usage of models like Claude. It wraps API endpoints for creating messages, streaming responses, and managing parameters in a type-safe TS environment. The library is designed for server-side use, interfacing with REST, and is stable for integration in web services or backend agents. Example usage shows how to instantiate the Anthropic client, call... -
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Godot MCP
MCP server for interfacing with Godot game engine
...It acts as a bridge between AI systems and the Godot editor, providing capabilities such as launching projects, running games in debug mode, and capturing runtime output for analysis. 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. -
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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AI-Tutorials/Implementations Notebooks
Codes/Notebooks for AI Projects
AI-Tutorials/Implementations Notebooks repository is a comprehensive collection of artificial intelligence tutorials and implementation examples intended for developers, students, and researchers who want to learn by building practical AI projects. The repository contains numerous Jupyter notebooks and code samples that demonstrate modern techniques in machine learning, deep learning, data science, and large language model workflows. It includes implementations for a wide range of AI topics such as computer vision, agent systems, federated learning, distributed systems, adversarial attacks, and generative AI. Many of the tutorials focus on building AI agents, multi-agent systems, and workflows that integrate language models with external tools or APIs. ... -
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Deepnote
Deepnote is a drop-in replacement for Jupyter
Deepnote is an open-source collaborative data science notebook platform designed as a modern alternative to traditional Jupyter notebooks. The project provides an AI-first computational environment where users can write, analyze, and share code, data, and visualizations in a single integrated workspace. Built on top of the Jupyter kernel ecosystem, it maintains compatibility with existing notebook workflows while introducing additional features focused on collaboration and automation. The system supports programming languages such as Python, R, and SQL and allows users to execute and analyze data directly within interactive notebooks. ... -
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Machine Learning Foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics
Machine Learning Foundations repository contains the code, notebooks, and teaching materials used in Jon Krohn’s Machine Learning Foundations curriculum. The project focuses on explaining the fundamental mathematical and computational concepts that underpin modern machine learning and artificial intelligence systems. The materials cover essential topics such as linear algebra, calculus, statistics, and probability, which form the theoretical basis of many machine learning algorithms. ... -
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minbpe
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm
minbpe is a minimal, clean implementation of byte-level Byte Pair Encoding (BPE), the tokenization approach widely used in modern language models. It operates on UTF-8 encoded bytes rather than Unicode characters, which makes it robust to arbitrary text inputs and avoids needing a language-specific character vocabulary. The repository is structured as a teaching-oriented implementation that shows how to train a tokenizer by learning merge rules, then apply those merges to encode text into... -
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Hello-Agents
Building an Intelligent Agent from Scratch
...It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems. -
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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SkillForge
Ultimate meta-skill for generating best-in-class Claude Code skills
SkillForge is a systematic methodology and tooling framework for creating high-quality AI “skills” specifically optimized for Claude Code integrations, treating skill creation as an engineering discipline rather than an ad-hoc art form. It introduces a multi-phase architecture where every input or request is triaged intelligently, analyzed deeply through structured lenses, specified formally, synthesized with automated generation, and finally subjected to multi-agent review before consideration complete. ... -
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agentation
The visual feedback tool for agents
...Instead of describing UI elements in text — like “the blue button in the sidebar” — users click directly on elements to automatically capture selectors, positions, and contextual metadata that can be consumed by AI agents to locate exact code references. This approach dramatically improves clarity and reduces ambiguity when working with AI tools that generate or modify UI code, making the handoff between human design intent and AI execution much clearer. The package installs into a React app and shows a floating toolbar that lets you activate element selection and add notes during a development session, helping you capture precise targets for improved AI output. -
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MiniMind-V
"Big Model" trains a visual multimodal VLM with 26M parameters
MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. MiniMind-V combines techniques from modern vision-language modeling but focuses on efficiency and simplicity so that individuals or small teams can explore multimodal learning without massive GPU clusters. ... -
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Sled
Teleport Claude Code, Codex or Gemini CLI to your phone
Sled under the layercodedev account appears to be a lightweight web and mobile UI aimed at interacting with local coding agents, likely including AI-assisted coding models or remote execution integrations; it’s designed in TypeScript/JavaScript and intended to let developers use or control coding agents from various devices. Although specific details in the repository are limited without direct project documentation, context and related online mentions indicate it functions as a local... -
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handson-ml
Teaching you the fundamentals of Machine Learning in python
...The examples underscore fundamentals like bias-variance trade-offs, regularization, and proper validation, grounding learners before they move to deep nets. Even though the deep learning stack evolved, the classical ML sections remain highly relevant for production data problems. The code is crafted to be clear rather than clever, prioritizing readability for newcomers. As a historical snapshot and a still-useful primer, it pairs well with the second edition for understanding how the ecosystem matured. -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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OpenAI Quickstart Node
Node.js example app from the OpenAI API quickstart tutorial
...The project is a practical starting point for building AI-powered applications, serving as a foundation for experimentation and integration into larger projects. It simplifies onboarding by offering step-by-step setup instructions and ready-to-use code snippets that can be adapted for custom needs. -
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HybridClaw
The enterprise operating layer for open agents
HybridClaw is an emerging open-source framework focused on enabling hybrid AI agent systems that combine local execution, tool integration, and multi-agent orchestration into a cohesive development environment. It is designed to work alongside modern agent ecosystems such as OpenClaw, Claude Code, and similar agentic coding tools, providing a flexible infrastructure for managing agent behaviors, workflows, and capabilities. The project emphasizes modularity, allowing developers to define and compose “skills” or capabilities that agents can invoke dynamically, enabling more adaptive and context-aware automation. HybridClaw aims to bridge the gap between isolated AI tools and fully orchestrated agent systems by enabling communication, coordination, and shared context across multiple agents or processes. ... -
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self-llm
Tutorial tailored for Chinese babies on rapid fine-tuning
self-llm is an open source educational project created by the Datawhale community that serves as a practical guide for deploying, fine-tuning, and using open-source large language models on Linux systems. The repository focuses on helping beginners and developers understand how to run and customize modern LLMs locally rather than relying solely on hosted APIs. It provides step-by-step tutorials covering environment setup, model deployment, inference workflows, and efficient fine-tuning... -
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CoAI.Dev
Next Generation AI One-Stop Internationalization Solution
...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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LLaMA Models
Utilities intended for use with Llama models
...The project’s issues and releases reflect an actively used coordination point for the ecosystem, where guidance, utilities, and compatibility notes are published. It complements separate repos that carry code and demos (for example inference kernels or cookbook content) by keeping authoritative metadata and specs here. Model lineages and size variants are documented externally (e.g., Llama 3.x and beyond), with this repo providing the “single source of truth” links and utilities. In practice, teams use llama-models as a reference when selecting variants, aligning licenses, and wiring in helper scripts for deployment. -
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apfel
Apple Intelligence from the command line
...Its architecture likely avoids over-engineering, making it suitable for small projects, prototypes, or educational purposes. The project encourages direct interaction with code rather than relying on extensive abstraction layers, giving developers more control over implementation details. -
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Rust Port
The Rust workspace under rust/ is the current systems-language port
Rust Port is an open-source reconstruction and experimentation framework derived from leaked or reverse-engineered versions of advanced AI coding agents, designed to replicate and extend the capabilities of agentic development systems. It functions as a programmable coding assistant that operates through autonomous workflows, enabling users to generate, modify, and analyze code with minimal manual intervention. The project emphasizes agent-based execution, where tasks are broken down into steps and handled iteratively, simulating how modern AI coding tools operate in production environments. It is often used as a sandbox for exploring how large-scale coding agents behave, including their decision-making processes, tool usage, and workflow orchestration. ... -
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TorchCode
Practice implementing softmax, attention, GPT-2 and more
...The platform provides a collection of curated problems that cover fundamental topics such as activation functions, normalization layers, attention mechanisms, and full transformer architectures. It runs in a Jupyter-based environment, allowing users to write, test, and debug their code interactively while receiving immediate feedback. An automated judging system evaluates correctness, gradient flow, and numerical stability, helping users understand both functional and theoretical aspects of their implementations. -
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Docker Agent
AI Agent Builder and Runtime by Docker Engineering
Docker Agent is an open-source multi-agent runtime developed by Docker that enables developers to define, run, and orchestrate AI agents using simple declarative configuration files instead of traditional code-heavy approaches. It introduces a YAML-based configuration model where users describe agent behavior, tools, models, and interaction logic in a single file, significantly reducing complexity in building AI systems. The runtime supports multi-agent collaboration, allowing specialized agents to delegate tasks to each other and operate as coordinated systems rather than isolated units. ... -
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NLP
Open source NLP guide with models, methods, and real use cases
...Designed for accessibility, the project evolves over time, allowing updates and improvements as NLP techniques advance. It reflects a practical approach to learning, where readers can explore code, experiment with models, and build foundational skills in machine learning-driven language processing.
