Search Results for "search engine optimization" - Page 2
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Showing 163 open source projects for "search engine optimization"
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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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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Google Kubernetes Engine (GKE) Samples
Sample applications for Google Kubernetes Engine (GKE)
Google Kubernetes Engine (GKE) Samples repository is a comprehensive collection of sample applications and reference implementations designed to demonstrate how to build, deploy, and manage workloads on Google Kubernetes Engine (GKE). It serves as a practical companion to official GKE tutorials, providing real, runnable code that illustrates how containerized applications are packaged, deployed, and scaled within Kubernetes clusters. -
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Robin
AI-powered tool for dark web OSINT search and investigation
Robin is an AI-powered open source tool designed to assist investigators and researchers in conducting dark web OSINT (Open Source Intelligence) investigations. It combines automated dark web search capabilities with large language models (LLMs) to analyze and summarize information discovered across hidden services and Tor-based search engines. The tool helps refine investigative queries, collect results from multiple dark web sources, and filter relevant intelligence using AI-driven... -
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marqo
Tensor search for humans
A tensor-based search and analytics engine that seamlessly integrates with your applications, websites, and workflows. Marqo is a versatile and robust search and analytics engine that can be integrated into any website or application. Due to horizontal scalability, Marqo provides lightning-fast query times, even with millions of documents. Marqo helps you configure deep-learning models like CLIP to pull semantic meaning from images. -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
...OptScale allows ML teams to multiply the number of ML/AI experiments running in parallel while efficiently managing and minimizing costs associated with cloud and infrastructure resources. OptScale MLOps capabilities include ML model leaderboards, performance bottleneck identification and optimization, bulk run of ML/AI experiments, experiment tracking, and more. The solution enables ML/AI engineers to run automated experiments based on datasets and hyperparameter conditions within the defined infrastructure budget. Certified FinOps solution with the best cloud cost optimization engine, providing rightsizing recommendations, Reserved Instances/Savings Plans, and dozens of other optimization scenarios. ... -
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.
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Nano-vLLM
A lightweight vLLM implementation built from scratch
...Despite its compact design, nano-vllm incorporates advanced optimization techniques such as prefix caching, tensor parallelism, and CUDA graph execution to achieve high performance during model inference. The engine is intended primarily for educational use, experimentation, and lightweight deployments where a full production-grade inference stack may be unnecessary. Its API closely mirrors that of the original vLLM framework, allowing developers familiar with vLLM to adopt the tool with minimal changes. -
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Open Notebook
An Open Source implementation of Notebook LM with more flexibility
...Designed to be self-hosted, it ensures complete data sovereignty by keeping your content local or within your own infrastructure. The platform supports 16+ AI providers—including OpenAI, Anthropic, Ollama, Google, and LM Studio—allowing flexible model choice and cost optimization. Open Notebook enables users to organize and analyze multi-modal content such as PDFs, videos, audio files, web pages, and Office documents. It combines full-text and vector search with context-aware AI chat to deliver insights grounded in your own research materials. With advanced features like multi-speaker podcast generation, customizable content transformations, and a comprehensive REST API, Open Notebook provides a powerful and extensible research environment. -
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vLLM
A high-throughput and memory-efficient inference and serving engine
vLLM is a fast and easy-to-use library for LLM inference and serving. High-throughput serving with various decoding algorithms, including parallel sampling, beam search, and more. -
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Windrecorder
Windrecorder is a memory search app by records everything
Windrecorder is an open-source personal memory search engine that continuously records on-screen activity in a highly optimized and storage-efficient format. It captures screen content locally and builds a searchable database using OCR and image understanding, allowing users to rewind and rediscover anything they have previously seen. The system indexes only meaningful visual changes, extracting text, browser data, and contextual information to improve search accuracy and reduce storage overhead. ... -
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LightLLM
LightLLM is a Python-based LLM (Large Language Model) inference
LightLLM is a high-performance inference and serving framework designed specifically for large language models, focusing on lightweight architecture, scalability, and efficient deployment. The framework enables developers to run and serve modern language models with significantly improved speed and resource efficiency compared to many traditional inference systems. Built primarily in Python, the project integrates optimization techniques and ideas from several leading open-source... -
$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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All-in-RAG
Big Model Application Development Practice 1
All-in-RAG is an open-source educational project designed to teach developers how to build applications using retrieval-augmented generation techniques. The repository provides a structured learning path that covers both theoretical foundations and practical implementation steps for RAG systems. It explains the full development pipeline required to create knowledge-aware AI assistants, including data preparation, document indexing, vector embedding generation, and retrieval strategies. The... -
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DocuBrowse
This does for Documents what repo-browser does for repos
DocuBrowse is a local AI-powered document search engine for personal or professional file collections. It indexes documents such as PDFs, Word files, spreadsheets, presentations, ebooks, HTML, text, and Markdown. The system combines SQLite FTS5 keyword search with local semantic embeddings for meaning-based retrieval. Users can click search results to generate an AI synopsis before opening the original file. -
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Newton
An open-source, GPU-accelerated physics simulation engine
Newton is a high-performance, GPU-accelerated physics simulation engine designed primarily for robotics research, machine learning, and advanced simulation workflows. Built on top of NVIDIA Warp, it leverages GPU parallelism to deliver scalable and efficient simulation environments that support rapid iteration and experimentation. The engine extends previous simulation frameworks by introducing differentiable physics capabilities, allowing it to integrate seamlessly with machine learning models and optimization pipelines. ... -
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MuJoCo
Multi-Joint dynamics with Contact. A general purpose physics simulator
MuJoCo, developed and maintained by Google DeepMind, is a high-performance physics engine designed for simulating complex, articulated systems that interact through contact. It is widely used in research fields such as robotics, biomechanics, computer graphics, animation, and machine learning, where fast and accurate physics simulations are essential. The engine provides a robust C API optimized for real-time computation, making it suitable for scientific research and advanced simulation... -
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BCEmbedding
Netease Youdao's open-source embedding and reranker models
BCEmbedding is NetEase Youdao’s open-source embedding and reranker model project for retrieval-augmented generation workflows. It includes an EmbeddingModel for semantic vector generation and a RerankerModel for refining and ordering search results. The project is optimized for bilingual and cross-lingual retrieval, especially across Chinese and English. It is used as a foundation for RAG systems such as QAnything and other Youdao products. The models are designed to work directly without... -
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Databend
Cloud-native open source data warehouse for analytics and AI queries
...It is designed with a separation of compute and storage, allowing compute nodes to scale independently while storing data in object storage systems. This architecture enables cost-efficient storage and elastic scaling for workloads that involve large datasets and complex queries. Databend provides a unified engine capable of handling analytics, vector search, and full-text search within a single platform. Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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Robyn
Experimental, AI/ML-powered and open sourced Marketing Mix Modeling
Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of... -
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Youtu-Agent
A simple yet powerful agent framework that delivers with models
Youtu-Agent is an open-source framework developed to simplify the creation, execution, and evaluation of autonomous AI agents. The system focuses on reducing the complexity traditionally involved in configuring large language model agents by providing a modular architecture that separates execution environments, tools, and context management. This structure allows developers to rapidly assemble agent systems capable of performing tasks such as research, file processing, and data analysis.... -
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IPRanges
Daily updated lists of cloud, bot, and service IP ranges
...It also tracks IP ranges used by search engine bots and automated agents including Googlebot, Bingbot, and OpenAI’s GPTBot. Lists are published in both IPv4 and IPv6 formats and are regularly updated through automated processes to keep the data current. In addition to provider specific lists, the project also offers merged and combined datasets that aggregate ranges from multiple sources into a single file. -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
Basic Memory is an open source knowledge system that turns AI conversations into persistent, structured knowledge you control. Instead of losing context after each chat, it stores information as simple Markdown files on your device, allowing both you and AI to read and write to the same knowledge base. It uses the Model Context Protocol (MCP) so compatible AI tools can access, update, and build on your notes across sessions. Basic Memory creates a semantic knowledge graph by linking related... -
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FLAML
A fast library for AutoML and tuning
...Users can find their desired customizability from a smooth range: minimal customization (computational resource budget), medium customization (e.g., scikit-style learner, search space, and metric), or full customization (arbitrary training and evaluation code). It supports fast automatic tuning, capable of handling complex constraints/guidance/early stopping. FLAML is powered by a new, cost-effective hyperparameter optimization and learner selection method invented by Microsoft Research. -
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JS Analyzer
Burp Suite extension for JavaScript static analysis
...The extension is designed to reduce manual effort when analyzing large or obfuscated JavaScript assets, helping testers find security vulnerabilities and sensitive information faster and more reliably. It also includes UI features such as live search, result filtering, and the ability to export findings in JSON format for further processing. The underlying engine can be used independently in Python, enabling integration into custom workflows or automated pipelines outside Burp Suite. -
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PaddleNLP
Easy-to-use and powerful NLP library with Awesome model zoo
PaddleNLP It is a natural language processing development library for flying paddles, with Easy-to-use text area API, Examples of applications for multiple scenarios, and High-performance distributed training Three major features, aimed at improving the modeling efficiency of the flying oar developer's text field, aiming to improve the developer's development efficiency in the text field, and provide rich examples of NLP applications. Provide rich industry-level pre-task capabilities... -
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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.... -
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Ungoogled Chromium
A lightweight approach to removing Google web service dependency
In descending order of significance (i.e. most important objective first), ungoogled-chromium is Google Chromium, sans dependency on Google web services, ungoogled-chromium retains the default Chromium experience as closely as possible. Unlike other Chromium forks that have their own visions of a web browser, ungoogled-chromium is essentially a drop-in replacement for Chromium. ungoogled-chromium features tweaks to enhance privacy, control, and transparency. However, almost all of these...
