Search Results for "sourceforge.net/projects/winpython/files/winpython_3.8/3.8.10.0/winpython64-3.8.10.0.7z" - Page 8
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Showing 825 open source projects for "sourceforge.net/projects/winpython/files/winpython_3.8/3.8.10.0/winpython64-3.8.10.0.7z"
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Paladin Point of Sale is a powerful retail management system designed to simplify daily store operations for independent retailers.Paladin Point of Sale is ideal for independent retailers in hardware, lumber, pharmacy, and specialty retail industries seeking an easy-to-use, industry-specific POS system with strong support and flexibility.
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Managed File Transfer SoftwareFor too many businesses, complex file transfer needs make it difficult to create, manage and support data flows to and from internal and external systems. Progress® MOVEit® empowers enterprises to take control of their file transfer workflows with solutions that help secure, simplify and centralize data exchanges throughout the organization.
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Framelink MCP for Figma
MCP server enabling AI coding tools to access Figma design data
Figma-Context-MCP is an open source server that connects Figma design data with AI-powered coding tools through the Model Context Protocol (MCP). It allows coding assistants to retrieve structured information from Figma files so they can better translate visual designs into working code. Instead of relying on screenshots or manual descriptions, Figma-Context-MCP accesses layout, styling, and component metadata directly from the Figma API and presents it in a simplified format optimized for AI models. This transformation reduces unnecessary metadata and focuses on the most relevant design attributes, helping AI coding agents produce more accurate UI implementations. ... -
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Style-Bert-VITS2
Style-Bert-VITS2: Bert-VITS2 with more controllable voice styles
...The project targets both power users and beginners: Windows users without Git or Python can install and run it using bundled .bat scripts, while advanced users can work with virtual environments, uv, and Python tooling. It includes a full GUI editor to script dialogue, set different styles per line, edit dictionaries, and save/load projects, plus a separate web UI and Colab notebooks for training and experimentation. 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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Ghidra MCP
Socket based MCP Server for Ghidra
GhidraMCP is a Ghidra plugin implementing the Model Context Protocol, bridging Ghidra's reverse engineering capabilities with AI assistants to enhance binary analysis tasks. -
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apfel
Apple Intelligence from the command line
...Apfel may include utilities or structural patterns that streamline development workflows, particularly in environments where speed and clarity are more important than feature richness. 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. -
Cloudbrink Personal SASE serviceCloudbrink’s Personal SASE is a high-performance connectivity and security service that delivers a lightning-fast, in-office experience to the modern hybrid workforce anywhere. Combining high-performance ZTNA with Automated Moving Target Defense (AMTD), and Personal SD-WAN all connections are ultra-secure.
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AI_Tutorial
A selection of learning materials, search, recommendation, advertising
...The project functions as a centralized knowledge base designed to help engineers and researchers discover tutorials, technical articles, algorithm explanations, and architecture discussions from across the AI ecosystem. Rather than focusing on a single framework or course, the repository collects materials from many sources such as open-source projects, technical blogs, research papers, and industry engineering posts. The curated content includes topics like recommendation systems, search engine architecture, neural networks, graph neural networks, and modern deep learning techniques. The goal of the project is to reduce information fragmentation by organizing valuable AI resources into structured sections that can be explored easily by learners and practitioners. -
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ggml
Tensor library for machine learning
...The project emphasizes portability and performance, enabling machine learning inference across a wide range of hardware environments including CPUs and specialized accelerators. It is widely used as a foundational component in projects that run large language models locally, including tools that perform inference for transformer-based models. The library also implements optimization algorithms and computation graph functionality so developers can build training and inference workflows directly on top of its tensor operations. -
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Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore cutting-edge techniques directly from the teams that developed them. The repository includes datasets, training scripts, and model implementations that support academic study and applied experimentation. ... -
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BMad Method
Breakthrough Method for Agile Ai Driven Development
...It transforms AI from a reactive assistant into a structured team of specialized roles such as product manager, architect, developer, and QA, each operating within predefined workflows. The system guides users through phases including analysis, planning, solution design, and implementation, ensuring that projects are approached systematically rather than through ad hoc prompting. It adapts dynamically to project complexity, offering lightweight flows for small tasks and more rigorous processes for enterprise-scale systems. The framework also emphasizes repeatability and consistency by storing workflows, templates, and roles as reusable artifacts. ... -
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Norfair
Lightweight Python library for adding real-time multi-object tracking
...This includes detectors performing tasks such as object or keypoint detection. It can easily be inserted into complex video processing pipelines to add tracking to existing projects. At the same time, it is possible to build a video inference loop from scratch using just Norfair and a detector. Supports moving camera, re-identification with appearance embeddings, and n-dimensional object tracking. Norfair provides several predefined distance functions to compare tracked objects and detections. The distance functions can also be defined by the user, enabling the implementation of different tracking strategies. -
Atera IT AutopilotIT Autopilot takes the pressure off your team by handling first-tier support across the channels your end users already live in — email, chat, Slack, Teams, and your Customer Portal. It doesn’t just respond to end-user queries, issues, and crises — it solves them.
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OP Vault
Give ChatGPT long-term memory using the OP Stack
OP Vault is an open-source system designed to give large language models long-term memory by enabling them to interact with a custom knowledge base built from user-provided documents. It combines a backend written in Go with a React frontend, allowing users to upload files such as PDFs, text documents, and books to create a searchable repository of information. The system uses vector databases like Pinecone alongside OpenAI models to index and retrieve relevant content, enabling precise question-answering grounded in the uploaded materials. Users can query the system in natural language and receive answers that include references to specific files and sections, improving transparency and trust in the responses. ... -
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Just the Browser
Remove AI features, telemetry data reporting, sponsored content
Just the Browser is a configuration and automation tool that helps users strip away unwanted features from mainstream web browsers like Chrome, Edge, and Firefox, focusing on removing AI integrations, telemetry reporting, sponsored content, and other built-in annoyances so that the browser behaves more like a pure web client. Instead of modifying browser binaries, it applies supported group policies and configuration files that disable intrusive UI elements, data collection features, default pop-ups, and integrated services, giving users more control over privacy and interface simplicity. It includes setup scripts for Windows and Mac/Linux, and directories with manual configuration files that explain what each setting does, allowing power users to tailor the experience. ... -
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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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DeepSeek VL
Towards Real-World Vision-Language Understanding
...The model is likely used internally as the visual encoder backbone for agent use cases, to ground perception in downstream tasks (e.g. answering questions about a screenshot). The repository includes model weights (or pointers to them), evaluation metrics on standard vision + language benchmarks, and configuration or architecture files. It also supports inference tools for forwarding image + prompt through the model to produce text output. DeepSeek-VL is a predecessor to their newer VL2 model, and presumably shares core design philosophy but with earlier scaling, fewer enhancements, or capability tradeoffs. -
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Binary Ninja MCP
A Binary Ninja plugin, MCP server
The Binary Ninja MCP is a plugin and bridge that integrates Binary Ninja with Large Language Model clients via the Model Context Protocol, enhancing reverse engineering workflows with AI assistance. -
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Codebuff
Generate code from the terminal!
...Instead of relying on a single model, it orchestrates multiple specialized agents that collaborate to understand, plan, edit, and review code changes. This multi-agent approach enables more accurate edits, better context awareness, and fewer errors across complex projects. Codebuff operates primarily through a CLI, allowing developers to interact with their code directly from the terminal. It also offers an SDK for integrating agent-based coding workflows into applications and development pipelines. With support for multiple AI models and customizable agents, Codebuff provides a flexible and powerful alternative to traditional coding assistants. -
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HumanLayer
Open source IDE for orchestrating AI coding agents in large codebases
HumanLayer is an open source development environment designed to help developers orchestrate and manage AI coding agents working within complex software projects. It provides a framework and tooling that allow AI agents to research, plan, and implement changes in large codebases while maintaining structured workflows. It focuses on enabling AI-assisted development through coordinated agent workflows rather than isolated code generation tasks. HumanLayer integrates with modern AI models and coding assistants to automate tasks such as code research, planning, and implementation while maintaining a structured development process. ... -
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dataline
AI data analysis and visualization on CSV, Postgres, MySQL, Snowflake
...The system enables both technical and non-technical users to explore data by asking questions conversationally, which the platform translates into database queries and analytical operations. It supports connections to multiple structured data sources such as PostgreSQL, MySQL, Snowflake, SQLite, Excel files, CSV datasets, and other database systems. Once connected, users can generate tables, charts, and reports automatically based on queries produced by the AI engine. The platform is designed with a privacy-first architecture that stores data locally on the user’s device rather than sending it to external cloud services by default. ... -
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ClawHost
Deploy OpenClaw with one click
...With built-in billing support via integrations like Polar.sh, users can manage subscriptions and invoicing directly from the platform, enabling it to serve both personal projects and small business use cases. -
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DGL
Python package built to ease deep learning on graph
...Fast and memory-efficient message passing primitives for training Graph Neural Networks. Scale to giant graphs via multi-GPU acceleration and distributed training infrastructure. DGL empowers a variety of domain-specific projects including DGL-KE for learning large-scale knowledge graph embeddings, DGL-LifeSci for bioinformatics and cheminformatics, and many others. We are keen to bringing graphs closer to deep learning researchers. We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. ... -
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Simd Library
C++ image processing and machine learning library with using of SIMD
...The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows and Linux, MSVS, G++ and Clang compilers, MSVS projects, and CMake build systems. -
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Telegram.Bot
.NET Client for Telegram Bot API
Telegram.Bot is the most popular .NET Client for Telegram Bot API. The Bot API is an HTTP-based interface created for developers keen on building bots for Telegram. Check Bots: An introduction for developers to understand what a Telegram bot is and what it can do. All Bot API methods are already documented by Telegram but this book covers all you need to know to create a chatbot in .NET. There are also many concrete examples written in C#. The guides here can even be useful to bot developers... -
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GitHub MCP Server
GitHub's official MCP Server
The GitHub MCP Server exposes GitHub as a Model Context Protocol server so AI assistants can safely act on repos, issues, pull requests, gists, and more through a consistent tool interface. It’s designed to run locally or remotely and then be attached to MCP-capable clients (for example, Copilot Chat) so an LLM can search code, open files, create branches, draft PRs, label or triage issues, and query metadata without hard-coding GitHub APIs. The server defines tools and resources with fine-grained scopes, leaning on GitHub’s auth to enforce least privilege and auditable access. It supports both stdio and HTTP transports, enabling IDE and headless integrations, and adopts common MCP behaviors like prompts, schemas, and tool definitions to keep agent calls predictable. ... -
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1Panel
1Panel provides an intuitive web interface and MCP Server
1Panel is a comprehensive Linux server management dashboard and MCP server built in Go. It offers UI control over websites, containers, databases, file systems, LLMs, backups, and monitoring, streamlining typical admin workflows via web. -
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CL4R1T4S
Archive of leaked AI system prompts and internal instruction sets
...Its stated goal is to promote transparency by documenting the hidden prompt scaffolding that shapes how AI systems behave and respond to users. CL4R1T4S organizes these materials by company or product, with directories containing prompt files and related instructions for many well-known AI systems. These files typically include text documents that represent internal system messages, tool instructions, or operational guidelines that influence model responses. According to the its description, the initiative is motivated by the idea that understanding the input instructions behind an AI system helps users better interpret its outputs. ... -
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Gradle MCP Server
A Model Context Protocol (MCP) server
The Gradle MCP Server is a Model Context Protocol implementation that enables AI tools to interact programmatically with Gradle projects. It uses the Gradle Tooling API to query project information and execute tasks, facilitating seamless integration with AI-driven development tools.
