Showing 838 open source projects for "artificial intelligent agent python"

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  • 1
    AgentGPT

    AgentGPT

    🤖 Assemble, configure & deploy autonomous AI Agents in your browser

    🤖 Assemble, configure, and deploy autonomous AI Agents in your browser. 🤖 AgentGPT allows you to configure and deploy Autonomous AI agents. Name your own custom AI and have it embark on any goal imaginable. It will attempt to reach the goal by thinking of tasks to do, executing them, and learning from the results 🚀. By sponsoring this free, open-source project, you not only have the opportunity to have your avatar/logo featured below, but also get the exclusive chance to chat with the...
    Downloads: 8 This Week
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  • 2
    WebArena

    WebArena

    Code repo for "WebArena to build Autonomous Agents

    WebArena is a realistic web environment designed for building and testing autonomous agents, providing a platform for developing web-based AI agents.
    Downloads: 0 This Week
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  • 3
    README-AI

    README-AI

    README file generator, powered by AI

    README-AI is an automated documentation generator that creates structured README files for GitHub repositories using AI-powered analysis.
    Downloads: 0 This Week
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  • 4
    DevOpsGPT

    DevOpsGPT

    Multi agent system for AI-driven software development

    Welcome to the AI Driven Software Development Automation Solution, abbreviated as DevOpsGPT. We combine LLM (Large Language Model) with DevOps tools to convert natural language requirements into working software. This innovative feature greatly improves development efficiency, shortens development cycles, and reduces communication costs, resulting in higher-quality software delivery. The automated software development process significantly reduces delivery time, accelerating software...
    Downloads: 0 This Week
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  • 5
    Generative Agents

    Generative Agents

    Generative Agents: Interactive Simulacra of Human Behavior

    Generative Agents is the research implementation behind a simulation of computational agents that exhibit believable human-like behavior. It combines a Python-based agent simulation with a browser-accessible game environment representing a small virtual town. Agents operate through stored memories and language-model-driven behavior while moving and interacting inside the environment. Users can start new simulations, advance them by configurable time steps, and save their progress for later...
    Downloads: 2 This Week
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  • 6
    LangChain Apps on Production with Jina

    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...
    Downloads: 0 This Week
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  • 7
    AI-Agent-Host

    AI-Agent-Host

    The AI Agent Host is a module-based development environment.

    The AI Agent Host integrates several advanced technologies and offers a unique combination of features for the development of language model-driven applications. The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI...
    Downloads: 0 This Week
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  • 8
    PromethAI

    PromethAI

    Open-source framework that gives you AI Agents

    PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis.
    Downloads: 0 This Week
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  • 9
    AutoGPT-Next-Web

    AutoGPT-Next-Web

    Assemble, configure, and deploy autonomous AI Agents in your browser

    One-Click to deploy well-designed AutoGPT-Next-Web web UI on Vercel.
    Downloads: 0 This Week
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  • 10
    Free-Auto-GPT

    Free-Auto-GPT

    Free AutoGPT enables autonomous AI tasks without paid APIs

    Free Auto GPT is an open source project that delivers a simplified version of an autonomous AI agent capable of completing tasks independently. 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...
    Downloads: 8 This Week
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  • 11
    ReactAgent

    ReactAgent

    The open-source React.js Autonomous LLM Agent

    React-Agent is a framework for integrating AI-driven agents into React applications. It provides an intuitive way to build interactive UI components powered by AI models, enabling dynamic and intelligent user interfaces.
    Downloads: 0 This Week
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  • 12
    langchain-prefect

    langchain-prefect

    Tools for using Langchain with Prefect

    Large Language Models (LLMs) are interesting and useful  -  building apps that use them responsibly feels like a no-brainer. Tools like Langchain make it easier to build apps using LLMs. We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. It provides a framework for creating deployments on a whole...
    Downloads: 0 This Week
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  • 13
    ParlAI

    ParlAI

    A framework for training and evaluating AI models

    ParlAI is a comprehensive research platform for building, training, and evaluating dialogue agents across a wide variety of tasks and datasets. It provides a unified interface—agents, teachers, and worlds—so the same model can be trained on multi-turn chit-chat, question answering, task-oriented dialogue, retrieval, or safety-focused datasets without changing core code. The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with...
    Downloads: 1 This Week
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  • 14
    Jason is a fully-fledged interpreter for an extended version of AgentSpeak, a BDI agent-oriented logic programming language, and is implemented in Java. Using JADE a multi-agent system can be distributed over a network effortlessly. This project was moved to https://jason-lang.github.io
    Downloads: 12 This Week
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  • 15
    AEA Framework

    AEA Framework

    A framework for autonomous economic agent (AEA) development

    agents-aea by Fetch.ai is a framework for building autonomous economic agents (AEAs) that can act independently, communicate, and transact on decentralized networks. It focuses on enabling AI-driven agents to participate in digital marketplaces and ecosystems.
    Downloads: 0 This Week
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  • 16
    TradeMaster

    TradeMaster

    TradeMaster is an open-source platform for quantitative trading

    TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream...
    Downloads: 0 This Week
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  • 17
    Multi-Agent Particle Envs

    Multi-Agent Particle Envs

    Code for a multi-agent particle environment used in a paper

    Multiagent Particle Environments is a lightweight framework for simulating multi-agent reinforcement learning tasks in a continuous observation space with discrete action settings. It was originally developed by OpenAI and used in the influential paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The environment provides simple particle-based worlds with simulated physics, where agents can move, communicate, and interact with each other. Scenarios are designed to...
    Downloads: 0 This Week
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  • 18
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no...
    Downloads: 0 This Week
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  • 19
    Video Pre-Training

    Video Pre-Training

    Learning to Act by Watching Unlabeled Online Videos

    The Video PreTraining (VPT) repository provides code and model artifacts for a project where agents learn to act by watching human gameplay videos—specifically, gameplay of Minecraft—using behavioral cloning. The idea is to learn general priors of control from large-scale, unlabeled video data, and then optionally fine-tune those priors for more goal-directed behavior via environment interaction. The repository contains demonstration models of different widths, fine-tuned variants (e.g. for...
    Downloads: 0 This Week
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  • 20
    PySC2

    PySC2

    StarCraft II learning environment

    PySC2 is DeepMind's Python component of the StarCraft II Learning Environment (SC2LE). It exposes Blizzard Entertainment's StarCraft II Machine Learning API as a Python RL Environment. This is a collaboration between DeepMind and Blizzard to develop StarCraft II into a rich environment for RL research. PySC2 provides an interface for RL agents to interact with StarCraft 2, getting observations and sending actions. The easiest way to get PySC2 is to use pip. That will install the pysc2...
    Downloads: 1 This Week
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  • 21
    RLCard

    RLCard

    Reinforcement Learning / AI Bots in Card (Poker) Games

    RLCard is a toolkit for reinforcement learning research on card games. It includes several popular card games and focuses on learning algorithms for imperfect information games like poker and blackjack.
    Downloads: 0 This Week
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  • 22
    Acme

    Acme

    A library of reinforcement learning components and agents

    Acme is a framework from DeepMind for building scalable and reproducible reinforcement learning agents. It emphasizes modular components, distributed training, and ease of experimentation.
    Downloads: 0 This Week
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  • 23
    Google Research Football

    Google Research Football

    Check out the new game server

    Google Research Football is a reinforcement learning environment simulating soccer matches. It focuses on learning complex behaviors such as team collaboration and strategy formation in competitive settings.
    Downloads: 0 This Week
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  • 24
    e-Dokyumento

    e-Dokyumento

    e-Dokyumento is web-based Document Management System (DMS)

    e-Dokyumento is opensource web-based Document Management System (DMS) A Document Management which automates the basic office document workflow such as receiving, filing, routing, and approving through capturing (scanning), digitizing (OCR Reading), storing, tagging, and electronically routing and approving (e-signature) of electronic documents. # Demo : https://e-dokyumento.herokuapp.com/ https://edokyu.seillig.com/ (refer to Readme.md for the...
    Downloads: 0 This Week
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  • 25
    Procgen

    Procgen

    Procedurally-Generated Game-Like Gym-Environments

    Procgen (short for Procedural Generation Benchmark) is a suite of 16 procedurally generated, game-like reinforcement learning environments designed to evaluate generalization and sample efficiency in RL agents. Unlike fixed, deterministic environments, Procgen generates new levels (layouts, obstacles, visual variation) each episode, making it impossible for an agent to simply memorize trajectories. The environments are designed to run very quickly (thousands of steps per second on a single...
    Downloads: 2 This Week
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