Search Results for "python windows" - Page 32
Sort By:
Showing 3021 open source projects for "python windows"
View related business solutions-
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
-
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
1
Google Workspace MCP Server
Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms
Google Workspace MCP is an open-source server that connects AI assistants to Google Workspace services through the Model Context Protocol (MCP), allowing large language models to interact directly with productivity tools. The project exposes a wide set of Google services including Gmail, Google Drive, Docs, Sheets, Slides, Calendar, Chat, and other Workspace components as structured tools that an AI system can call programmatically. By acting as a bridge between AI clients and the Google... -
2
Chitu
High-performance inference framework for large language models
Chitu is a high-performance inference engine designed to deploy and run large language models efficiently in production environments. The framework focuses on improving efficiency, flexibility, and scalability for organizations that need to run LLM inference workloads across different hardware platforms. It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations.... -
3
Streamer-Sales
LLM Large Model of Selling Anchor
Streamer-Sales is an open-source large language model system designed specifically for e-commerce live streaming and automated product promotion. The project focuses on generating persuasive product descriptions and live presentation scripts that mimic the style of professional online sales hosts. By analyzing product characteristics and marketing information, the model can produce engaging explanations that emphasize benefits, features, and emotional appeal to encourage viewers to make... -
4
FlagEmbedding
Retrieval and Retrieval-augmented LLMs
FlagEmbedding is an open-source toolkit for building and deploying high-performance text embedding models used in information retrieval and retrieval-augmented generation systems. The project is part of the BAAI FlagOpen ecosystem and focuses on creating embedding models that transform text into dense vector representations suitable for semantic search and large language model pipelines. FlagEmbedding includes a family of models known as BGE (BAAI General Embedding), which are designed to... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
-
5
CoPaw
Your Personal AI Assistant; easy to install, deploy on local or coud
CoPaw is a personal AI assistant designed to run on your own machine or in the cloud, giving you full control over memory, models, and data. Built by the AgentScope team, it connects to multiple chat platforms—including DingTalk, Feishu, QQ, Discord, iMessage, and more—through a single unified assistant. CoPaw supports both cloud-based LLM providers and fully local models such as llama.cpp, MLX, and Ollama, allowing you to operate without API keys if preferred. It includes a browser-based... -
6
Flowly AI
Flowly is 100x faster than OpenClaw
Flowly is an open-source personal AI assistant that runs locally on your machine and connects to multiple communication platforms like Telegram, WhatsApp, Discord, and Slack. It acts as a centralized AI system that can perform tasks such as web browsing, file management, command execution, scheduling, and more—all while keeping your data private. Designed for flexibility, Flowly supports multiple AI providers and models through LiteLLM, allowing users to customize how their assistant... -
7
Open-AutoGLM
An open phone agent model & framework
Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off... -
8
Qwen-Image
Qwen-Image is a powerful image generation foundation model
Qwen-Image is a powerful 20-billion parameter foundation model designed for advanced image generation and precise editing, with a particular strength in complex text rendering across diverse languages, especially Chinese. Built on the MMDiT architecture, it achieves remarkable fidelity in integrating text seamlessly into images while preserving typographic details and layout coherence. The model excels not only in text rendering but also in a wide range of artistic styles, including... -
9
Telegram Media Downloader
Download media files from a telegram conversation/chat/channel
Download media files from a telegram conversation/chat/channel up to 2GiB per file. -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
10
LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application,... -
11
KServe
Standardized Serverless ML Inference Platform on Kubernetes
KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and... -
12
Xorbits Inference
Replace OpenAI GPT with another LLM in your app
Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop. Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits... -
13
Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase,... -
14
SHAP
A game theoretic approach to explain the output of ml models
SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions. While SHAP can explain the output of any machine learning model, we have developed a high-speed exact algorithm for tree ensemble methods. Fast C++ implementations are supported for XGBoost, LightGBM, CatBoost, scikit-learn and pyspark... -
15
Pixel2Motion
AI logo animation skill: turn raster logos into smooth SVG animation
Pixel2Motion is an AI-assisted logo animation project that turns raster brand assets into clean, motion-ready SVG animations. It starts with a PNG, JPG, WebP, or screenshot logo and reconstructs it as a smooth vector design. The project then adds structured SVG motion, animated HTML demos, and preview outputs for review. It is built for designers and developers who need polished logo reveals without manually rebuilding every asset from scratch. Its workflow emphasizes visual quality,... -
16
PaLM + RLHF - Pytorch
Implementation of RLHF (Reinforcement Learning with Human Feedback)
PaLM-rlhf-pytorch is a PyTorch implementation of Pathways Language Model (PaLM) with Reinforcement Learning from Human Feedback (RLHF). It is designed for fine-tuning large-scale language models with human preference alignment, similar to OpenAI’s approach for training models like ChatGPT. -
17
BudouX
Standalone, small, language-neutral
Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning-powered line break organizer tool. It is standalone. It works with no dependency on third-party word segmenters such as Google cloud natural language API. It is small. It takes only around 15 KB including its machine learning model. It's reasonable to use it even on the client-side. It is language-neutral. You can train a model for any language by feeding a dataset to BudouX’s training... -
18
dtreeviz
Python library for decision tree visualization & model interpretation
A python library for decision tree visualization and model interpretation. Decision trees are the fundamental building block of gradient boosting machines and Random Forests(tm), probably the two most popular machine learning models for structured data. Visualizing decision trees is a tremendous aid when learning how these models work and when interpreting models. The visualizations are inspired by an educational animation by R2D3; A visual introduction to machine learning. Please see How to... -
19
Netron
Visualizer for neural network, deep learning, machine learning models
...Netron has experimental support for TensorFlow, PyTorch, TorchScript, OpenVINO, Torch, Arm NN, BigDL, Chainer, CNTK, Deeplearning4j, MediaPipe, ML.NET, scikit-learn, TensorFlow.js. There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser. -
20
AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,... -
21
sunnypilot
Open source driver assistance system
sunnypilot is an open-source driver-assistance system derived from comma.ai’s openpilot and designed primarily for comma 3 and 3X hardware. It supports hundreds of vehicle makes and models while modifying how steering, acceleration, braking, and cruise assistance behave. Its Modular Assistive Driving System provides more flexible engagement behavior than the upstream project. Neural-network lateral control, automatic lane changes, and configurable driving models expand steering... -
22
ADR
ADR secures enterprise AI agents through observability
ADR, short for Agentic AI Detection and Response, is an enterprise security system for monitoring and evaluating AI agents. It captures agent intent, tool activity, and execution traces from coding assistants, internal automations, and customer-facing agents. A normalized sensor layer provides observability across multiple agent tools and operating systems. ADR-Bench supplies more than 300 realistic tasks, 133 MCP servers, and coverage of 17 documented agent attack techniques. Its two-tier... -
23
Vedana
Open source multi-agent RAG over a knowledge graph
Vedana is an open-source multi-agent RAG system built around a typed knowledge graph. It is designed for questions that require structure, completeness, and traceability instead of simple text similarity. The system lets agents navigate data step by step through Cypher queries, vector search, document lookup, and source verification. Its architecture combines a knowledge graph, pgvector-based embeddings, incremental ETL, and a backoffice interface for chat, metrics, prompt tuning, and data... -
24
OpenHarness
Open Agent Harness with a built-in personal agent, Ohmo
OpenHarness is an open-source framework developed to support large-scale machine learning workflows, particularly in the context of training, evaluating, and benchmarking AI models. It provides a structured environment for orchestrating experiments, managing datasets, and standardizing evaluation processes across different models. The project focuses on reproducibility and scalability, allowing researchers and engineers to run consistent experiments while tracking results effectively. It... -
25
HolyClaude
AI coding workstation: Claude Code + web UI + 5 AI CLIs + headless
HolyClaude is a developer-focused toolkit designed to enhance and extend the capabilities of Claude Code environments by providing structured prompts, utilities, and workflow enhancements for AI-assisted coding. The project centers around improving how developers interact with AI agents, enabling more efficient code generation, debugging, and task execution through optimized prompt engineering. It includes predefined templates and interaction patterns that guide the AI toward producing more...
