Search Results for "linux operating systems" - Page 30
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Showing 1501 open source projects for "linux operating systems"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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$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.
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OpenAI Realtime Embedded
Instructions on how to use the Realtime API on Microcontrollers
openai-realtime-embedded is a repository that provides resources, SDKs, and example links for using OpenAI’s Realtime API on embedded hardware platforms (e.g. microcontrollers). The goal is to enable low-latency conversational agents (e.g. voice-based assistants) running directly on constrained devices, by leveraging WebRTC and streaming APIs to communicate with OpenAI systems. The repo includes pointers to an ESP32 implementation (maintained as esp32 branch) and documentation that Espressif... -
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DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning,...
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Best-of Machine Learning with Python
A ranked list of awesome machine learning Python libraries
This curated list contains 900 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml. Contributions are very welcome! General-purpose machine learning and deep learning... -
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E2B Cookbook
Examples of using E2B
...The examples illustrate how developers can build AI workflows capable of performing tasks such as data analysis, code execution, and application generation inside isolated sandbox environments. E2B itself provides secure Linux-based sandboxes that enable AI systems to safely run generated code and interact with real computing resources without compromising the host environment. The cookbook organizes examples across multiple frameworks and model providers, allowing developers to experiment with integrations involving models from OpenAI, Anthropic, and other ecosystems. -
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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MolmoWeb
Open multimodal web agent built by Ai2
MolmoWeb is an open-source multimodal web agent designed to autonomously navigate and interact with web browsers using vision-language models, representing a significant step toward fully agentic AI systems that can operate in real-world digital environments. The system takes natural language instructions and translates them into sequences of browser actions such as clicking, typing, scrolling, and navigating, effectively performing tasks on behalf of the user. Unlike traditional automation... -
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GalTransl
Automated translation solution for visual novels
GalTransl is an automated translation system specifically designed for visual novels, particularly those in the “galgame” genre, leveraging large language models to streamline and enhance the translation process. It integrates support for multiple advanced LLM providers such as GPT-4, Claude, DeepSeek, and other models, enabling high-quality, context-aware translations that go beyond traditional machine translation approaches. The platform is built to handle the unique structure of visual... -
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Shadcn UI v4 MCP Server
A mcp server to allow LLMS gain context about shadcn ui component
Shadcn UI v4 MCP Server is a Model Context Protocol server that enables AI assistants to access, retrieve, and utilize shadcn/ui component libraries within development workflows, effectively bridging UI component systems with AI-driven coding tools. It provides structured access to component source code, demos, metadata, and reusable UI blocks, allowing AI agents to generate accurate and production-ready interface implementations. The server supports multiple frontend frameworks including... -
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ToolUniverse
Democratizing AI scientists with ToolUniverse
ToolUniverse is a comprehensive open-source ecosystem designed to transform any large language model into an autonomous “AI scientist” capable of performing real scientific research tasks through structured tool interaction. It standardizes how AI systems discover, select, and execute tools by introducing a unified AI-Tool Interaction Protocol that allows models to seamlessly connect with hundreds of scientific resources, including machine learning models, datasets, APIs, and analytical... -
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Agent Starter Pack
Ship AI Agents to Google Cloud in minutes, not months
Agent Starter Pack is a production-focused framework that provides pre-built templates and infrastructure for rapidly developing and deploying generative AI agents on Google Cloud. It is designed to eliminate the complexity of moving from prototype to production by bundling essential components such as deployment pipelines, monitoring, security, and evaluation tools into a single package. Developers can create fully functional agent projects with a single command, generating both backend and... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Rig
Rust framework for building modular and scalable LLM-powered apps
Rig is an open source Rust framework designed to help developers build modular and scalable applications powered by large language models. It provides a unified set of abstractions that allow applications to interact with many AI model providers and vector databases through a single interface. Its architecture emphasizes modularity, enabling developers to integrate only the components and integrations they need for a specific application. Rig includes built-in support for agent workflows,... -
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Advanced NLP with spaCy
Advanced NLP with spaCy: A free online course
Advanced NLP with spaCy is an open-source educational repository that provides the materials for an interactive course on advanced natural language processing using the spaCy library. The course is designed to teach developers how to build real-world NLP systems by combining rule-based techniques with machine learning models. The repository includes lessons, exercises, and examples that guide learners through tasks such as tokenization, named entity recognition, text classification, and... -
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AIGC-Interview-Book
AIGC algorithm engineer interview secrets
AIGC-Interview-Book is a large educational repository designed to help engineers prepare for technical interviews related to artificial intelligence and generative AI roles. The project compiles knowledge from industry practitioners and researchers into a structured reference covering the AI ecosystem. Topics included in the repository span large language models, generative AI systems, traditional deep learning methods, reinforcement learning, computer vision, natural language processing,... -
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rust-bert
Rust native ready-to-use NLP pipelines and transformer-based models
rust-bert is a Rust-based implementation of transformer-based natural language processing models that provides ready-to-use pipelines for tasks such as text classification, summarization, and question answering. The project ports many capabilities of the Hugging Face Transformers ecosystem into the Rust programming language. It allows developers to run state-of-the-art NLP models like BERT, GPT-2, and DistilBERT directly within Rust applications while maintaining high performance and memory... -
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machine learning tutorials
machine learning tutorials (mainly in Python3)
machine-learning is a continuously updated repository documenting the author’s learning journey through data science and machine learning topics using practical tutorials and experiments. The project presents educational notebooks that combine mathematical explanations with code implementations using Python’s scientific computing ecosystem. Topics covered include classical machine learning algorithms, deep learning models, reinforcement learning, model deployment, and time-series analysis.... -
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AiLearning-Theory-Applying
Quickly get started with AI theory and practical applications
AiLearning-Theory-Applying is a comprehensive educational repository designed to help learners quickly understand artificial intelligence theory and apply it in practical machine learning and deep learning projects. The repository provides extensive tutorials covering mathematical foundations, machine learning algorithms, deep learning concepts, and modern large language model architectures. It includes well-commented notebooks, datasets, and implementation examples that allow learners to... -
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face.evoLVe
High-Performance Face Recognition Library on PaddlePaddle & PyTorch
face.evoLVe is a high-performance face recognition library designed for research and real-world applications in computer vision. The project provides a comprehensive framework for building and training modern face recognition models using deep learning architectures. It includes components for face alignment, landmark localization, data preprocessing, and model training pipelines that allow developers to construct end-to-end facial recognition systems. The repository supports multiple neural... -
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Netflix Maestro
Netflix’s Workflow Orchestrator
Maestro is a large-scale workflow orchestration platform originally developed by Netflix to coordinate complex data processing and machine learning workflows across distributed systems. The system acts as a general-purpose workflow orchestrator that manages the execution, scheduling, monitoring, and recovery of large pipelines used for analytics and AI operations. It was designed to support the demanding internal infrastructure of Netflix, where thousands of workflows must process massive... -
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MyScaleDB
A @ClickHouse fork that supports high-performance vector search
MyScaleDB is an open-source SQL vector database designed for building large-scale AI and machine learning applications that require both analytical queries and semantic vector search. The system is built on top of the ClickHouse database engine and extends it with specialized indexing and search capabilities optimized for vector embeddings. This design allows developers to store structured data, unstructured text, and high-dimensional vector embeddings within a single database platform.... -
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Prompt Poet
Streamlines and simplifies prompt design for both developers
Prompt Poet is an open-source framework designed to simplify the creation, organization, and maintenance of prompts for large language model applications. The project focuses on transforming prompt engineering into a structured design process rather than ad-hoc string manipulation within application code. It allows developers and non-technical users to build prompts using templated configurations based on YAML and Jinja2, which makes prompts easier to compose, reuse, and modify across... -
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Generative AI for beginners with JS
Join a time-traveling adventure where you meet history’s legends
Generative AI with JavaScript is an educational repository created by Microsoft that teaches developers how to build applications powered by large language models using the JavaScript ecosystem. The project is structured as a multi-lesson curriculum that introduces the concepts, tools, and practical techniques required to create generative AI applications. Each lesson includes written explanations, hands-on exercises, quizzes, and supporting videos to help developers learn the material... -
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PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
PicoLM is an open-source inference framework designed to run large language models on extremely constrained hardware environments such as inexpensive single-board computers and embedded systems. The project focuses on enabling efficient local inference by optimizing memory usage, computation, and system dependencies so that relatively large models can operate on devices with minimal RAM. It is written primarily in C and designed with a minimalist architecture that removes unnecessary... -
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RAG from Scratch
Demystify RAG by building it from scratch
RAG From Scratch is an educational open-source project designed to teach developers how retrieval-augmented generation systems work by building them step by step. Instead of relying on complex frameworks or cloud services, the repository demonstrates the entire RAG pipeline using transparent and minimal implementations. The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into... -
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AgentEvolver
Towards Efficient Self-Evolving Agent System
AgentEvolver is an open-source research framework for building self-evolving AI agents powered by large language models. The system focuses on improving the efficiency and scalability of training autonomous agents by allowing them to generate tasks, explore environments, and refine strategies without heavy reliance on manually curated datasets. Its architecture combines reinforcement learning with LLM-driven reasoning mechanisms to guide exploration and learning. The framework introduces... -
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DriveLM
Driving with Graph Visual Question Answering
DriveLM is a research-oriented framework and dataset designed to explore how vision-language models can be integrated into autonomous driving systems. The project introduces a new paradigm called graph visual question answering that structures reasoning about driving scenes through interconnected tasks such as perception, prediction, planning, and motion control. Instead of treating autonomous driving as a purely sensor-driven pipeline, DriveLM frames it as a reasoning problem where models... -
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ReCall
Learning to Reason with Search for LLMs via Reinforcement Learning
ReCall is an open-source framework designed to train and evaluate language models that can reason through complex problems by interacting with external tools. The project builds on earlier work focused on teaching models how to search for information during reasoning tasks and extends that idea to a broader system where models can call a variety of external tools such as APIs, databases, or computation engines. Instead of relying purely on static knowledge stored inside the model, ReCall...
