Search Results for "virtual-machine"
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Showing 27 open source projects for "virtual-machine"
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autoresearch
AI agents autonomously run and improve ML experiments overnight
autoresearch is an experimental framework that enables AI agents to autonomously conduct machine learning research by iteratively modifying and training models. Created by Andrej Karpathy, the project allows an agent to edit the model training code, run short experiments, evaluate results, and repeat the process without human intervention. Each experiment runs for a fixed five-minute training window, enabling rapid iteration and consistent comparison across architectural or hyperparameter changes. ... -
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SafeClaw
Chat with it via text and voice
SafeClaw is an open-source, entirely local alternative to cloud-based AI assistants like OpenClaw, enabling users to build a personal assistant that runs on their own machine without incurring API usage charges or exposing data to third-party services. It emphasizes privacy and predictability by using traditional programming, rule-based intent parsing, and established machine learning tools rather than large language models, meaning there are no per-token API costs and deterministic behavior. The assistant offers features such as voice control using fully local speech-to-text (Whisper) and text-to-speech (Piper) capabilities, news aggregation with extractive summarization, and smart home or Bluetooth device control. ... -
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Hermes Agent
The agent that grows with you
Hermes Agent is a fully open-source autonomous AI agent designed to run persistently on your own machine or server, becoming more capable the longer it operates by learning from experience and building reusable procedural skills. Rather than functioning as a stateless chatbot, it maintains long-term memory across sessions and can generate searchable “Skill Documents” that capture how it solved complex tasks so it doesn’t start from scratch each time. -
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Semantic Router
Superfast AI decision making and processing of multi-modal data
Semantic Router is a superfast decision-making layer for your LLMs and agents. Rather than waiting for slow, unreliable LLM generations to make tool-use or safety decisions, we use the magic of semantic vector space — routing our requests using semantic meaning. Combining LLMs with deterministic rules means we can be confident that our AI systems behave as intended. Cramming agent tools into the limited context window is expensive, slow, and fundamentally limited. Semantic Router enables... -
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MindsDB
Making Enterprise Data Intelligent and Responsive for AI
MindsDB is an AI data solution that enables humans, AI, agents, and applications to query data in natural language and SQL, and get highly accurate answers across disparate data sources and types. MindsDB connects to diverse data sources and applications, and unifies petabyte-scale structured and unstructured data. Powered by an industry-first cognitive engine that can operate anywhere (on-prem, VPC, serverless), it empowers both humans and AI with highly informed decision-making... -
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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. -
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Dendrite
Tools to build web AI agents that can authenticate
Dendrite Python SDK is a toolkit for building web AI agents that can authenticate, interact with, and extract data from any website, facilitating web automation tasks. -
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Director
AI video agents framework for next-gen video interactions
Director is a video database management system designed to organize, search, and retrieve large collections of video content efficiently. -
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Cybergod
A program that can do anything to earn money without human operators
...It aims to simulate artificial general intelligence (AGI) by leveraging evolutionary algorithms, deep active inference, and other advanced AI techniques. The project explores the boundaries of machine autonomy and self-directed behavior in computational environments. -
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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Potpie
Create custom engineering agents for your codebase
Potpie is an AI-powered data analysis tool that automates the exploration and visualization of datasets, assisting users in uncovering insights without extensive coding. -
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NagaAgent
A simple yet powerful agent framework for personal assistants
NagaAgent is an experimental framework for building interactive virtual agents capable of autonomous reasoning, dialog, and task execution using components that mirror human cognitive patterns. It provides abstractions for representing goals, context, and state so that agents can plan sequences of actions, evaluate outcomes, and adjust behavior over time. The project includes mechanisms for semantic memory, reasoning pipelines, and integration points with external data sources and language models so that agents can interpret natural language instructions and produce coherent multi-step outputs. ... -
12
ChemCrow
Chemcrow
ChemCrow is an AI-powered framework designed to assist in chemical research and discovery. It integrates AI models with chemical knowledge bases to provide intelligent recommendations for synthesis planning, reaction prediction, and material discovery. This tool helps automate and accelerate research in computational chemistry and drug development. -
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TrustGraph
Deploy reasoning AI agents powered by agentic graph RAG in minutes
TrustGraph is an AI-driven framework designed to assess and visualize trust relationships within networks, aiding in the analysis of trustworthiness and influence among entities. -
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Burr
Build applications that make decisions. Chatbots, agents, simulations
Burr makes it easy to develop applications that make decisions (chatbots, agents, simulations, etc...) from simple python building blocks. Burr works well for any application that uses LLMs and can integrate with any of your favorite frameworks. Burr includes a UI that can track/monitor/trace your system in real-time, along with pluggable persisters (e.g. for memory) to save & load application state. -
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ClawTeam
ClawTeam: Agent Swarm Intelligence (One Command → Full Automation)
...These agents communicate, share insights, and dynamically adapt their strategies based on real-time feedback, creating a form of collective intelligence. The framework supports a wide range of use cases, including software development, machine learning research, financial analysis, and content production. It is designed to work with various AI tools and command-line agents, making it highly flexible and extensible. ClawTeam also includes monitoring tools such as dashboards and tmux-based views to observe agent activity and progress. -
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Dash Data Agent
Self-learning data agent that grounds its answers in layers of content
...It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live runtime context — to generate SQL queries that are both technically correct and semantically meaningful. The system then executes those queries against a database and interprets the results, returning human-friendly insights not just raw rows, while learning from errors and successes to reduce repeated mistakes. -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
...It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. ... -
18
airda
airda(Air Data Agent
airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes. -
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
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StudioOllamaUI
StudioOllamaUI is a local, portable interface for Ollama
...It doesn't clutter your registry or leave traces on your disk. AI for Everyone: No expensive GPU? No problem. Optimized to run smoothly on your CPU and RAM. Total Privacy: Everything stays on your machine. No data leaves for the cloud, and no hidden files are left on your system. -
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CodinIT.dev
Free, local, open-source AI app builder
CodinIT.dev is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5, Claude Sonnet 4.5) or local via Ollama, so you’re never locked in. ... -
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Adala
Adala: Autonomous DAta (Labeling) Agent framework
Adala is a data-centric AI framework focused on dataset curation, annotation, and validation. It helps AI teams manage high-quality training datasets by providing tools for data auditing, error detection, and quality assessment. -
23
Dragonfire
The open-source virtual assistant for Ubuntu based Linux distributions
Dragonfire is the open-source virtual assistant project for Ubuntu-based Linux distributions. Her main objective is to serve as a command and control interface to the helmet user. So that you will be able to give orders just by using your voice commands and your eye movements. That makes the helmet handsfree. We are planning to ship Dragonfire as a preinstalled software package on DragonOS Linux Distribution. -
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aCompute
Aims to enable researcher to tap in to mobile computing capability
This is a software agent based computing program that will enable researchers and other users to tap in computing power of machine available by sharing work load on the fly with zero configuration on network & resources A self organizing agent program that will understand network and its resource. where as the only job left to researcher is to split up jobs in several chunks of programs either parallel or sequential jobs and go issue the job (A visual Modeler or Scripting support need to be yet designed) Software agents will automatically manage the rest or resource management, sharing , cloning of tasks etc. ... -
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minder
Monitoring your infrastructure for free.
This software presents a flexible and configurable proposal for monitoring and management of real and virtual HPC infrastructures, compatible with paradigm of cloud computing. We help you to answer: 1) What is the performance of my resources? 2) What equipment and resources do we have already? 3) What do we need to upgrade or repair? 4) What can we consolidate to reduce complexity or reduce energy use? 5) What resources would be better reused somewhere else?
