Search Results for "execute" - Page 6
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Showing 167 open source projects for "execute"
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Streamline Azure Security with Palo Alto Networks VM-SeriesImprove your security posture and reduce incident response time. Use the VM-Series to natively analyze Azure traffic and dynamically drive policy updates based on workload changes.
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MuJoCo MPC
Real-time behaviour synthesis with MuJoCo, using Predictive Control
MuJoCo MPC (MJPC) is an advanced interactive framework for real-time model predictive control (MPC) built on top of the MuJoCo physics engine, developed by Google DeepMind. It allows researchers and roboticists to design, visualize, and execute complex control tasks for simulated or real robotic systems. MJPC integrates a high-performance GUI and multiple predictive control algorithms, including iLQG, gradient descent, and Predictive Sampling — a competitive, derivative-free method that achieves robust real-time control. The system supports multi-shooting optimization, enabling precise motion planning across diverse domains like quadruped locomotion, humanoid tracking, and dexterous manipulation. ... -
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ToRA
Tool-integrated Reasoning LLM Agents
...Instead of relying solely on text generation, the system dynamically invokes tools such as symbolic solvers or programming libraries when deeper computation is required. This approach allows the model to reason step by step in natural language and then execute precise calculations or code through tool calls, creating a hybrid reasoning workflow. The framework was designed to address known weaknesses of large language models in mathematical problem solving and formal reasoning tasks. Training data includes tool-use trajectories that teach the model when to reason verbally and when to delegate tasks to specialized tools. -
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Ailice
AIlice is a fully autonomous, general-purpose AI agent
AIlice is an open-source autonomous AI agent framework built to function as a general-purpose assistant that can plan, decompose, and execute complex tasks through a structured multi-agent architecture. The project presents itself as a standalone assistant powered by open-source language models, with an internal design that treats user requests almost like executable programs rather than simple chat prompts. Its core IACT architecture allows the system to break large goals into smaller sub-tasks, assign them to dynamically created agents, and combine the results with a focus on resilience and fault tolerance. ... -
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Functionary
Chat language model that can use tools and interpret the results
...Function definitions are typically provided in JSON schema format, allowing the model to generate structured function calls compatible with modern tool-calling interfaces used in AI applications. Functionary can decide whether to execute tools sequentially or in parallel and can analyze the outputs of those tools to produce context-aware responses. This capability allows AI systems to interact with external services, APIs, or computation engines rather than relying solely on knowledge embedded in the model. -
Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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XAgent
An Autonomous LLM Agent for Complex Task Solving
XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications. -
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AutoGPT.js
Auto-GPT on the browser
...Unlike traditional AutoGPT implementations that require server infrastructure, AutoGPT.js is designed to run primarily in the browser, making it easier to deploy and experiment with autonomous agents. The platform uses web APIs and language model integrations to give the agent the ability to plan tasks, execute commands, and store short-term memory during operations. Developers can also configure the system to connect to different language model APIs and adjust parameters such as temperature or prompt configuration. The project demonstrates how autonomous AI agents can operate within modern web environments while maintaining user privacy and accessibility. -
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gptee
LLMs done the UNIX-y way
...Now supporting GPT3.5 chat completions! gptee was designed for use within shell scripts and other programs and also works in interactive shells. You can compose commands and execute them in a script. Proceed with caution before running arbitrary shell scripts. Using a chat completion model (like gpt-3.5-turbo), you can then inject a system message with -s or --system messages. For davinci and other non-chat models, the output is prefixed to the prompt. Compose shell commands like you would in a script. Try with a custom model. ... -
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Petals
Run 100B+ language models at home, BitTorrent-style
...Single-batch inference runs at ≈ 1 sec per step (token) — up to 10x faster than offloading, enough for chatbots and other interactive apps. Parallel inference reaches hundreds of tokens/sec. Beyond classic language model APIs — you can employ any fine-tuning and sampling methods, execute custom paths through the model, or see its hidden states. You get the comforts of an API with the flexibility of PyTorch. You can also host BLOOMZ, a version of BLOOM fine-tuned to follow human instructions in the zero-shot regime — just replace bloom-petals with bloomz-petals. Petals runs large language models like BLOOM-176B collaboratively — you load a small part of the model, then team up with people serving the other parts to run inference or fine-tuning. -
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LangChain Apps on Production with Jina
Langchain Apps on Production with Jina & FastAPI
Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own... -
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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FlubuCore
A cross platform build and deployment automation system
...This gives you code completion, IntelliSense, debugging, FlubuCore custom analyzers, and native access to the whole .NET ecosystem inside of your scripts. FlubuCore offers a .net (core) console application that uses power of roslyn to compile and execute scripts. Intuitive and easy to learn. C#, fluent interface, and IntelliSense make even the most complex script creation a breeze. Large number of often used built-in tasks like e.g. versioning, running tests, creating deployment packages, publishing NuGet packages, docker tasks, git tasts, sql tasks, npm tasks, executing PowerShell, managing IIS scripts and many more. -
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GPT-Code UI
An open source implementation of OpenAI's ChatGPT Code interpreter
An open source implementation of OpenAI's ChatGPT Code interpreter. Simply ask the OpenAI model to do something and it will generate & execute the code for you. You can put a .env in the working directory to load the OPENAI_API_KEY environment variable. For Azure OpenAI Services, there are also other configurable variables like deployment name. See .env.azure-example for more information. Note that model selection on the UI is currently not supported for Azure OpenAI Services. -
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Chinese-LLaMA-Alpaca-2 v2.0
Chinese LLaMA & Alpaca large language model + local CPU/GPU training
...At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which significantly improves the model's ability to understand and execute instructions. -
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llm-chain
Rust crate for building chains in large language models
...With llm-chain, you can focus on building powerful AI applications. Create reusable and easily customizable prompt templates for consistent and structured interactions with LLMs. Build powerful chains of prompts that allow you to execute more complex tasks, step by step, leveraging the full potential of LLMs. Provides seamless integration with LLaMa models, enabling natural language understanding and generation tasks with Facebook's research models. Incorporates support for Stanford's Alpaca models, expanding the range of available language models for advanced AI applications. ... -
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Free-Auto-GPT
Free AutoGPT enables autonomous AI tasks without paid APIs
...It allows users to run an AutoGPT-style system without relying on paid OpenAI APIs, making it more accessible for experimentation and personal use. Free Auto GPT can take a goal, break it into smaller steps, and execute actions in a loop to achieve results with minimal human input. Designed for ease of use, the project focuses on removing cost barriers while still demonstrating how autonomous agents function. It is suitable for developers, learners, and hobbyists who want to explore AI-driven automation without subscription requirements. It provides a lightweight implementation that highlights core AutoGPT concepts such as task decomposition, iteration, and independent execution in a simplified environment. -
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Pyrogram
Elegant, modern and asynchronous Telegram MTProto API framework
...Type-hinted: Types and methods are all type-hinted, enabling excellent editor support. Async: Fully asynchronous (also usable synchronously if wanted, for convenience). Powerful: Full access to Telegram's API to execute any official client action and more. -
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Chameleon LLM
Codes for "Chameleon: Plug-and-Play Compositional Reasoning
Discover Chameleon, our cutting-edge compositional reasoning framework designed to enhance large language models (LLMs) and overcome their inherent limitations, such as outdated information and lack of precise reasoning. By integrating various tools such as vision models, web search engines, Python functions, and rule-based modules, Chameleon delivers more accurate, up-to-date, and precise responses, making it a game-changer in the natural language processing landscape. With GPT-4 at its... -
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chatgpt-web
Privatized web program based on ChatGPT3.5 API
This project can deploy your own customized ChatGPT web program (compatible with gpt3.5) with one click, just download the project file of the corresponding platform in the release, modify the configuration and execute it, open http://127.0.0.1:8080, you can Get your own ChatGPT website. Note that each parameter may affect you to get a different chat effect, and you may get another answer if you change a parameter, so please try to debug it yourself, and don't complain about the artificial mental retardation when you come up. There are more than 20 parameter examples in the document, such as AI chatbot, product name generation, python code fixer, etc. -
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Ultroid
Telegram UserBot, Built in Python Using Telethon lib
Ultroid, a pluggable telegram userbot, made in python using Telethon! Ultroid has been written from scratch, making it more stable and less crashes. Ultroid warns you when you try to install/execute dangerous stuff (people nowadays make plugins to hack user accounts, Ultroid is safe). Unlike many others userbots that are being suspended by Heroku, Ultroid doesn't get suspended. Ultroid has been written from scratch, making it more stable and less of crashes. Error handling been done in the best way possible, such that the bot doesn't crash and stop all of a sudden. ... -
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AirSim
A simulator for drones, cars and more, built on Unreal Engine
AirSim is an open-source, cross platform simulator for drones, cars and more vehicles, built on Unreal Engine with an experimental Unity release in the works. It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a... -
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StudioGAN
StudioGAN is a Pytorch library providing implementations of networks
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation. StudioGAN aims to offer an identical playground for modern GANs so that machine learning researchers can readily compare and analyze a new idea. Moreover, StudioGAN provides an unprecedented-scale benchmark for generative models. The benchmark includes results from GANs (BigGAN-Deep, StyleGAN-XL), auto-regressive models (MaskGIT,... -
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Jarvis Python AI Assistant
Python AI assistant
Jarvis is a voice commanding assistant service in Python 3.8 It can recognize human speech, talk to user and execute basic commands. Opens a web page (e.g 'Jarvis open youtube') Play music in Youtube (e.g 'Jarvis play mozart') Increase/decrease the speakers master volume (also can set max/mute speakers volume) (e.g 'Jarvis volume up!') Opens libreoffice suite applications (calc, writer, impress) (e.g 'Jarvis open calc') Tells about something, by searching on the internet (e.g 'Jarvis tells me about oranges') Tells the weather for a place (e.g 'Jarvis tell_the_skills me the weather in London') Tells the current time and/or date (e.g 'Jarvis tell me time or date') Set an alarm (e.g 'Jarvis create a new alarm') Tells the internet speed (ping, uplink and downling) (e.g 'Jarvis tell_the_skills me the internet speed') Tells the internet availability (e.g 'Jarvis is the internet connection ok?') ... -
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Lucid
A collection of infrastructure and tools for research
...You can run the notebooks on your local machine, too. Clone the repository and find them in the notebooks subfolder. You will need to run a local instance of the Jupyter notebook environment to execute them. Feature visualization answers questions about what a network, or parts of a network, are looking for by generating examples. -
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uTensor
TinyML AI inference library
uTensor is an embedded machine learning inference framework designed to run neural network models on resource-constrained devices such as microcontrollers and Internet-of-Things hardware. The project focuses on enabling TinyML deployments by translating trained machine learning models into efficient C++ code that can execute directly on embedded systems. Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized inference kernels suitable for constrained environments. This approach allows developers to build machine learning models using standard frameworks and then deploy them to devices with extremely limited memory and processing power. ... -
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Olivia
Your new best friend powered by an artificial neural network
...All the data used by Olivia is saved in your client. Olivia is organized in modules to facilitate the addition of new capabilities. These modules can be written in Go to execute multiple tasks. The project is entirely open-source from the website to the backend. Thus you can build your own chatbot and contribute to Olivia. You can directly add the PWA to your home screen from the website, and you won't remember that it is a website running behind this native-like app. -
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imgaug
Image augmentation for machine learning experiments
imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions, hue/saturation changes, cropping/padding, blurring, etc. ...
