Search Results for "system data" - Page 9
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Showing 579 open source projects for "system data"
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MediaPipe Solutions
Cross-platform, customizable ML solutions
MediaPipe is an open-source framework developed by Google for building cross-platform machine learning pipelines that process audio, video, and other streaming data in real time. The system provides developers with tools and reusable components that allow them to combine multiple machine learning models with preprocessing and postprocessing logic into efficient perception pipelines. These pipelines can run on a wide variety of platforms including mobile devices, desktop systems, web browsers, and embedded edge devices. ... -
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Secure OpenClaw
A personal 24x7 AI assistant like OpenClaw
...It leverages Claude and other models to interpret messages and is built to manage persistent memory, scheduled reminders, and integration with hundreds of third-party apps to automate workflows without leaving your chat. The design emphasizes security and autonomy by allowing you to maintain ownership of your data and run the system within your trusted environment, while still harnessing advanced AI capabilities. -
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VGGT
[CVPR 2025 Best Paper Award] VGGT
...Rather than training separate networks per task, it shares an encoder and leverages geometric heads/decoders to infer structure and motion from images or short clips. The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose or depth), making the system more robust to challenging viewpoints and textures. The repo provides inference pipelines to estimate geometry from monocular inputs, stereo pairs, or brief sequences, together with evaluation harnesses for common geometry benchmarks. Training utilities highlight data curation and augmentations that preserve geometric cues while improving generalization across scenes and cameras. -
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Google Workspace MCP Server
Control Gmail, Google Calendar, Docs, Sheets, Slides, Chat, Forms
...Authentication is handled through OAuth-based flows that allow both single-user and multi-user environments while maintaining access control over Workspace data. -
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Hindsight
Hindsight: Agent Memory That Learns
...Instead of relying solely on vector similarity or basic retrieval techniques, Hindsight organizes information into distinct categories such as facts, experiences, beliefs, and observations, allowing agents to differentiate between raw data and inferred knowledge. The system operates through three core mechanisms—retain, recall, and reflect—which respectively handle storing information, retrieving relevant context, and generating new insights based on accumulated experience. -
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Easy DataSet
A powerful tool for creating datasets for LLM fine-tuning
...It supports ingesting domain-specific documents in a wide range of formats — including PDF, Markdown, DOCX, EPUB, and plain text — and can intelligently segment, clean, and structure content into rich datasets tailored for downstream LLM training needs. The system includes automated question-generation capabilities, hierarchical label trees, and answer generation pipelines that use LLM APIs to produce coherent paired data with customizable templates. Beyond dataset creation, Easy-dataset also provides a built-in evaluation system with model testing and blind-test features, helping teams validate model performance using curated test sets. -
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Hiring Agent
AI agent to evaluate and score resumes
...It reads a resume PDF and converts the content into Markdown-like text. It then uses a local or hosted language model to extract structured candidate information into sectioned JSON. The system can enrich that resume data with GitHub profile and repository signals when a profile is available. After the data is collected, it produces an explainable evaluation with category scores, supporting evidence, bonus points, and deductions. It can run locally with Ollama or use Google Gemini, which makes it flexible for teams that want either private local processing or hosted model access. -
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Thoth
Thoth - Personal AI Sovereignty. A local-first AI assistant
Thoth is an AI-driven system designed to support advanced reasoning, knowledge processing, or agentic workflows, likely inspired by the concept of structured intelligence and decision-making. It focuses on organizing and synthesizing information in a way that enables deeper insights and more autonomous behavior. The project may incorporate LLMs, data pipelines, and modular components to handle complex tasks such as reasoning, planning, or knowledge retrieval. -
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Alpamayo 1
Bridging Reasoning and Action Prediction
...The model is designed as a foundational component rather than a complete driving stack, allowing developers to build custom autonomous vehicle applications on top of it. It incorporates vision-language-action modeling, enabling it to process sensor data and contextual information simultaneously. Alpamayo supports tasks such as trajectory prediction, auto-labeling, and reasoning-based decision making. The system is optimized for high-performance GPU environments and is intended primarily for experimentation and benchmarking. Overall, it represents an advanced step toward integrating reasoning into autonomous driving pipelines. -
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autoresearch-win-rtx
AI agents running research on single-GPU nanochat training
...It adapts the original autoresearch concept to a Windows environment, enabling users to perform iterative machine learning optimization without requiring specialized Linux or data center setups. The system revolves around a small set of core files, including a training script that is continuously modified by an AI agent, along with supporting utilities for data preparation and evaluation. Experiments are executed within a fixed time budget, ensuring consistent benchmarking across iterations and allowing the agent to focus on incremental improvements. ... -
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OpenRecall
OpenRecall is a fully open-source, privacy-first alternative
...This data is then indexed into a searchable database, allowing users to retrieve past information quickly using natural language queries. Unlike proprietary alternatives, OpenRecall operates entirely locally, ensuring that all captured data remains on the user’s device and is never transmitted to external servers. The platform supports multiple operating systems, including Windows, macOS, and Linux, making it widely accessible across different environments. -
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NeMo Retriever Library
Document content and metadata extraction microservice
...It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient handling of large datasets. It supports multiple extraction strategies for different document formats, balancing accuracy and throughput depending on the use case. Additionally, it can generate embeddings for extracted content and integrate with vector databases like Milvus, making it well-suited for retrieval-augmented generation pipelines. -
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LLM Vision
Visual intelligence for your home.
...Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process events from surveillance platforms such as Frigate and convert them into meaningful summaries, notifications, or structured data for automation workflows. It also maintains a timeline of analyzed camera events that can be displayed in dashboards or queried through the assistant interface. -
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Plano
Delivery infrastructure for agentic apps
...The system provides intelligent LLM routing APIs that support model agility, along with filter chains for safety, moderation, and memory hooks. It also exposes rich traces, metrics, and logs to support continuous improvement of agent behavior in production. Overall, Plano functions as delivery infrastructure for scalable, maintainable AI agent systems. -
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Zero
Experience email the way you want with Mail0
Zero is an open-source AI-driven email platform that empowers users to self-host their own modern mail application while still connecting to external providers like Gmail or Outlook, offering flexibility for personal and business communication. It combines a unified inbox experience with privacy-first architecture so your email data stays under your control without third-party tracking or data harvesting. The system enhances traditional email workflows by integrating AI assistance for tasks such as summarizing messages, suggesting replies, prioritizing conversations, and helping users manage their inbox more intelligently. With a clean, customizable web interface built on modern technologies, Zero makes it pleasant to navigate mail, search through messages, and organize threads without feeling cluttered or slow. -
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autoresearch-macos
AI agents running research on single-GPU nanochat training
...The project typically includes components such as data preparation scripts, a training loop, and an instruction file that guides the agent’s behavior. By automating experimentation and optimization, it allows continuous improvement without manual intervention, effectively turning research into a self-improving process. -
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agent heroes
Generate, animate and schedule your AI characters
...It provides abstractions for defining agent behavior, communication patterns, and task execution pipelines, enabling developers to build systems that go beyond simple prompt-response interactions. The framework is designed to integrate with modern large language models and external APIs, allowing agents to access tools, retrieve data, and perform actions dynamically. It also supports modular design, making it possible to extend agent capabilities or swap components without redesigning the entire system. agentheroes is particularly useful for automation, workflow orchestration, and experimentation with collaborative AI systems. -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
...It provides collections of domain-specific modules and reference implementations that make it easier to pre-train, fine-tune, and deploy very large models on multi-GPU and multi-node infrastructure. NeMo 2.0 introduces a Python-based configuration system, replacing YAML with more flexible, programmable configs that can be versioned and composed for different experiments. The framework builds on PyTorch Lightning–style modular abstractions, so training scripts are composed from reusable components for data loading, models, optimizers, and schedulers, which simplifies experimentation and adaptation. ... -
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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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Utopia
World's first open-source enterprise world model
Utopia is an open-source enterprise world model designed to turn evolving organizational knowledge into a governed decision layer. It combines a bitemporal knowledge graph, editable ontology, retrieval, reasoning, and audit history in one self-hosted application. The system ingests documents and synchronized sources, then extracts entities and facts with provenance and validity intervals. Corrections preserve earlier versions instead of overwriting them. Hybrid search and chat work across... -
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clip-retrieval
Easily compute clip embeddings and build a clip retrieval system
clip-retrieval is an open-source toolkit designed to build large-scale semantic search systems for images and text by leveraging CLIP embeddings to enable multimodal retrieval. It allows developers to compute embeddings for both images and text efficiently and then index them for fast similarity search across massive datasets. The system is optimized for performance and scalability, capable of processing tens or even hundreds of millions of embeddings using GPU acceleration. It includes... -
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OP Vault
Give ChatGPT long-term memory using the OP Stack
...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. The project is designed to handle large volumes of data, making it suitable for personal knowledge management, research archives, or enterprise documentation systems. -
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AstronRPA
Agent-ready RPA suite with visual workflow automation tools engine
...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 operations and system integrations. Astron RPA includes a large library of reusable components that handle tasks such as user interface operations, data processing, and system interactions, allowing workflows to be assembled from modular building blocks. Astron RPA also integrates with intelligent agent systems so that automated processes and AI-driven workflows can work together in broader automation scenarios. -
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Floneum
Instant, controllable, local pre-trained AI models in Rust
Floneum is an open-source platform for building AI-powered workflows using large language models through a visual and extensible interface. The system allows users to design complex AI pipelines using a drag-and-drop workflow builder rather than writing extensive code. It focuses on enabling developers and researchers to create language model applications that combine different tools, data sources, and AI capabilities into automated workflows. Floneum supports a plugin architecture that allows external components to extend the platform while maintaining isolation and security. ... -
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OxidizeBot
High performance Twitch bot in Rust
...You own your data. It uses your internet for the best possible latency. It's light on system resources*. And running locally means it can perform rich interactions with your games like Chaos%.
