Search Results for "ai engine" - Page 2
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Showing 113 open source projects for "ai engine"
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LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. ... -
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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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Cactus
Low-latency AI inference engine optimized for mobile devices
Cactus is a low-latency, energy-efficient AI inference framework designed specifically for mobile devices and wearables, enabling advanced machine learning capabilities directly on-device. It provides a full-stack architecture composed of an inference engine, a computation graph system, and highly optimized hardware kernels tailored for ARM-based processors. Cactus emphasizes efficient memory usage through techniques such as zero-copy computation graphs and quantized model formats, allowing large models to run within the constraints of mobile hardware. ... -
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AutoCoder
A long-running autonomous coding agent powered by the Claude Agent
Autocoder is an experimental auto-generation engine that transforms high-level prompts or structured descriptions into functioning source code, models, or systems with minimal manual intervention. Rather than hand-writing boilerplate or repetitive patterns, users supply a specification—such as a description of a feature, a function prototype, or a module outline—and Autocoder fills in complete implementations that compile and run. It is built to support iterative refinement: after generating... -
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MCP Server Qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. ​ -
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OpenMemory
Local long-term memory engine for AI apps with persistent storage
OpenMemory is a self-hosted memory engine designed to provide long-term, persistent storage for AI and LLM-powered applications. It enables developers to give otherwise stateless models a structured memory layer that can store, retrieve, and manage contextual information over time. OpenMemory is built around a hierarchical memory architecture that organizes data into semantic sectors and connects them through a graph-based structure for efficient retrieval. -
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Rhino
On-device Speech-to-Intent engine powered by deep learning
Rhino is Picovoice's Speech-to-Intent engine. It directly infers intent from spoken commands within a given context of interest, in real-time. The end-to-end platform for embedding private voice AI into any software in a few lines of code. Design with no limits on top of a modular platform. Create use-case-specific voice AI models in seconds. Develop voice features with a few lines of code using intuitive and cross-platform SDKs. -
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OptScale
FinOps and MLOps platform to run ML/AI and regular cloud workloads
...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. With OptScale, users get complete cloud resource usage transparency, anomaly detection, and extensive functionality to avoid budget overruns. -
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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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Claude Blog
Claude Code blog skill suite
Claude Blog is a Claude Code blog skill suite for planning, writing, optimizing, and auditing long-form content. It is built as a full-lifecycle blog engine with 30 sub-skills, 5 agents, 12 content templates, on-demand references, Python scripts, and automated tests. The workflow is designed to produce production-ready content rather than one-shot AI drafts. It uses a five-gate delivery contract covering capability, format, visual quality, content review, and asset integrity. Commands support new blog posts, rewrites, content audits, briefs, editorial calendars, strategy, outlines, SEO checks, personas, taxonomy, multilingual workflows, research, audio narration, and Google data. ... -
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geo-seo-claude
GEO-first SEO skill for Claude Code
geo-seo-claude is an AI-powered tool designed to automate the creation of geographically optimized SEO content using large language models, helping businesses improve their visibility in local search results. It leverages AI to generate location-specific content tailored to different regions, allowing users to scale SEO efforts across multiple cities or markets without manual content creation. -
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Memori
SQL-native memory layer enabling persistent context for AI agents
Memori is an open source SQL-native memory engine designed to add persistent memory capabilities to AI applications, large language models, and multi-agent systems. It provides a memory layer that automatically captures conversations and interactions between users and AI models, allowing systems to retain knowledge across sessions instead of operating statelessly. It extracts structured information such as facts, preferences, rules, and summaries from interactions and stores them in standard SQL databases for later retrieval. ... -
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RedAmon
AI-powered framework for automated penetration testing and red teaming
...It begins with a multi-phase reconnaissance engine that maps the entire attack surface of a target, collecting information such as subdomains, open ports, services, and potential vulnerabilities. RedAmon then uses an AI agent orchestrator to analyze this data, select appropriate tools, and perform exploitation steps such as credential brute forcing or CVE-based attacks. All discovered assets, relationships, and vulnerabilities are stored in a Neo4j knowledge graph, allowing the system to reason about the environment and make informed decisions during the attack process. -
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AstrBot
Agentic IM Chatbot infrastructure
AstrBot is an AI-driven chatbot framework designed to help developers build intelligent conversational agents that can be deployed across multiple messaging environments. The project focuses on modular architecture so users can extend the bot with plugins, custom skills, and integrations without modifying the core engine. It is built to support modern large language model workflows, enabling natural language understanding, automated responses, and task execution within chat contexts. ... -
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Newton
An open-source, GPU-accelerated physics simulation engine
...It is developed as a Linux Foundation project with contributions from major organizations like NVIDIA, Google DeepMind, and Disney Research, highlighting its relevance in cutting-edge robotics and AI development. -
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jetson-stats
Simple package for monitoring and control your NVIDIA Jetson
...It supports Jetson platforms such as Orin, Xavier, Nano, TX, and newer Jetson families. The project includes jtop, a terminal-based dashboard that gives users a live view of CPU, GPU, memory, power, temperature, engine usage, and system status. It can also be imported into Python scripts, which makes it useful for custom monitoring, robotics dashboards, automation, and diagnostics. Developers working with embedded AI systems can use it to understand performance limits and troubleshoot hardware behavior during deployment. Its main value is giving Jetson users a practical, readable, and scriptable view of board health and resource usage. -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI... -
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Xtuner
A Next-Generation Training Engine Built for Ultra-Large MoE Models
...The engine supports training models with hundreds of billions of parameters and enables long-context training with sequence lengths reaching tens of thousands of tokens. Its architecture incorporates memory-efficient optimizations that allow researchers to train large models even when computational resources are limited. XTuner is also designed to integrate with modern AI ecosystems, supporting multimodal training, reinforcement learning optimization, and instruction tuning pipelines. -
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AstronRPA
Agent-ready RPA suite with visual workflow automation tools engine
Astron RPA is an enterprise-grade robotic process automation platform designed to help organizations and developers build automated workflows for desktop and web applications. It provides a visual workflow designer that supports low-code and no-code development, allowing users to create automation processes through a drag-and-drop interface instead of writing extensive code. It enables automation of common desktop software and browser-based tasks, making it suitable for repetitive business... -
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MLC LLM
Universal LLM Deployment Engine with ML Compilation
MLC LLM is a machine learning compiler and deployment framework designed to enable efficient execution of large language models across a wide range of hardware platforms. The project focuses on compiling models into optimized runtimes that can run natively on devices such as GPUs, mobile processors, browsers, and edge hardware. By leveraging machine learning compilation techniques, mlc-llm produces high-performance inference engines that maintain consistent APIs across platforms. The system... -
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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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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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WFGY 3.0
A tension reasoning engine over 131 S-class problems
WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply... -
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SEO Machine
A specialized Claude Code workspace for creating long-form
SEO Machine is an AI-powered content production system built as a structured workspace for generating long-form, SEO-optimized blog content through automated workflows. It integrates research, writing, analysis, and optimization into a single pipeline, allowing users to produce high-quality articles tailored to search engine performance. The system uses specialized commands and agents to perform tasks such as keyword research, competitor analysis, content drafting, and optimization. ... -
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Qwen3-ASR
Qwen3-ASR is an open-source series of ASR models
Qwen3-ASR is an automatic speech recognition system in the QwenLM family, developed to convert spoken language into text with strong accuracy and real-time performance. As a specialized ASR variant of the broader Qwen language model ecosystem, it focuses on capturing reliable transcriptions from audio sources such as recordings, live streams, or conversational inputs while supporting low latency use cases. The architecture combines advanced neural acoustic modeling with context-aware...