Open Source Python Intelligent Agents
Sort By:
Python Intelligent Agents
View 95 business solutionsBrowse free open source Python Intelligent Agents and projects below. Use the toggles on the left to filter open source Python Intelligent Agents by OS, license, language, programming language, and project status.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
Orchestrate Your AI Agents with ZenflowZenflow orchestrates AI agents like a real engineering system. With parallel execution, spec-driven workflows, and deep multi-repo understanding, agents plan, implement, test, and verify end-to-end. Upgrade to AI workflows that work the way your team does.
-
1
Self-Operating Computer
A framework to enable multimodal models to operate a computer
The Self-Operating Computer Framework is an innovative system that enables multimodal models to autonomously operate a computer by interpreting the screen and executing mouse and keyboard actions to achieve specified objectives. This framework is compatible with various multimodal models and currently integrates with GPT-4o, o1, Gemini Pro Vision, Claude 3, and LLaVa. Notably, it was the first known project to implement a multimodal model capable of viewing and controlling a computer screen. The framework supports features like Optical Character Recognition (OCR) and Set-of-Mark (SoM) prompting to enhance visual grounding capabilities. It is designed to be compatible with macOS, Windows, and Linux (with X server installed), and is released under the MIT license. -
2
AutoGPT
Powerful tool that lets you create and run intelligent agents
AutoGPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI. -
3
LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features. -
4
AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. -
A warehouse and inventory management software that scales with your business.Logiwa is a leader in cloud-native fulfillment technology, revolutionizing high-volume fulfillment for third-party logistics (3PLs), B2B and B2C fulfillment networks, and direct-to-consumer brands. Our flagship product, Logiwa IO, is an advanced Fulfillment Management System (FMS) designed to scale operations in the digital era. Logiwa elevates digital warehousing to new heights, ensuring dynamic and efficient fulfillment processes. Our commitment to AI-driven technology, combined with a focus on customer-centricity, equips businesses to adeptly navigate and excel in rapidly changing market landscapes. Discover the future of smart fulfillment and how you can fulfill brilliantly with Logiwa IO.
-
5
MetaGPT
The Multi-Agent Framework
The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs. -
6
smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
7
CrewAI
Framework for orchestrating role-playing, autonomous AI agents
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI provides the backbone for sophisticated multi-agent interactions. -
8
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. DragonOS will be a Linux distribution specially designed for the helmet. It will contain various software packages for controlling the helmet. It will be the first of its kind. Dragonfire uses Mozilla DeepSpeech to understand your voice commands and Festival Speech Synthesis System to handle text-to-speech tasks. -
9
SuperAGI
A dev-first open source autonomous AI agent framework
An open-source autonomous AI framework to enable you to develop and deploy useful autonomous agents quickly & reliably. Join a community of developers constantly contributing to make SuperAGI better. Access your agents through a graphical user interface. Interact with agents by giving them input, permissions, etc. Agents typically learn and improve their performance over time with feedback loops. Run multiple agents simultaneously to improve efficiency and productivity. Connect to multiple Vector DBs to enhance your agent’s performance. Each agent is unique, use different models of your choice. Get insights into your agent’s performance and optimize accordingly. Control token usage to manage costs effectively. Enable your agents to learn and adapt by storing their memory. Get notified when agents get stuck in the loop, and provide proactive resolution. Read and store files generated by Agents. -
Captain Compliance - Data Privacy and Compliance SoftwareCaptain Compliance handles your data privacy requirements so you can be privacy compliant. No more compliance stress, stop stressing over regulatory risks – just privacy protection managed by experts. Our user-friendly platform backed by privacy professionals simplifies the process of navigating regulations, giving your customers transparent choices, and building essential trust for your organization.
-
10
Composio
Composio equip's your AI agents & LLMs
Empower your AI agents with Composio - a platform for managing and integrating tools with LLMs & AI agents using Function Calling. Equip your agent with high-quality tools & integrations without worrying about authentication, accuracy, and reliability in a single line of code. -
11
SWE-agent
SWE-agent takes a GitHub issue and tries to automatically fix it
SWE-agent turns LMs (e.g. GPT-4) into software engineering agents that can resolve issues in real GitHub repositories. On the SWE-bench, the SWE-agent resolves 12.47% of issues, achieving state-of-the-art performance on the full test set. We accomplish our results by designing simple LM-centric commands and feedback formats to make it easier for the LM to browse the repository, and view, edit, and execute code files. We call this an Agent-Computer Interface (ACI). -
12
AutoGroq
Revolutionizes the way users interact with Autogen
AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen™ and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency. AutoGroq was born out of the realization that the traditional approach to building AI agents was backwards. Instead of creating agents in anticipation of problems, AutoGroq uses the syntax of the users' needs as the basis for constructing the perfect AI team. It's how we wished Autogen worked from the very beginning. With AutoGroq, a fully configured workflow, team of agents, and skillset are just a few clicks and a couple of minutes away, without any programming necessary. Our rapidly growing user base of nearly 8000 developers is a testament to the power and effectiveness of AutoGroq. -
13
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. -
14
PraisonAI
PraisonAI application combines AutoGen and CrewAI or similar framework
PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction. -
15
SalesGPT
Context-aware AI Sales Agent to automate sales outreach
This repo is an implementation of a context-aware AI Agent for Sales using LLMs and can work across voice, email and texting (SMS, WhatsApp, WeChat, Weibo, Telegram, etc.). SalesGPT is context-aware, which means it can understand what stage of a sales conversation it is in and act accordingly. Moreover, SalesGPT has access to tools, such as your own pre-defined product knowledge base, significantly reducing hallucinations. -
16
iX
Autonomous GPT-4 agent platform
IX is a platform for designing and deploying autonomous and [semi]-autonomous LLM-powered agents and workflows. IX provides a flexible and scalable solution for delegating tasks to AI-powered agents. Agents created with the platform can automate a wide variety of tasks while running in parallel and communicating with each other. -
17
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 mining sites and bringing to the base. At the time the agent is born, it doesn't know how to walk nor it knows that it feels pleasure by mining. He has tact only (blind agent). The video shows learning, planning, executing and plan optimization. -
18
Auto File Selection
Detect all the "important" files from your computer.
The main aim of this project is to design and develop a mechanism that can find all the “important” files inside a computer. -
19
This project has been moved to https://bitbucket.org/pbazant/evoversum/src/master/ . Evoversum is a fast Darwinian evolution simulator. The program simulates a 2D world populated with "animals" which struggle for food, reproduce and may also eat each other. The subject of evolution is their behavior, which may become quite complex. There is an updated video tutorial at http://www.youtube.com/watch?v=nPkZvyVDWJU !
-
20
-
21
PolyPlanet is an evolutionary playground inspired by Polyworld. It uses genetic algorithms to evolve the world and its inhabitants. Current inhabitants include PolyPlants, PolyTrees, and PolyDudes that have neural network brains which also evolve.
-
22
ANGie
Alice Next Generation (internet entity)
An AIML based chat bot building on the original Alice AIML 1.0.1 set produced by Dr. Wallace and the ALICE AI Foundation and the PyAIML code base written by Cort Stratton, the ANGie project incorporates additional AIML sets, adds its own AIML to the set, adds new AIML tags and additional code to provide more dynamic responses and more logical case-based-reasoning. Reading through most AIML sets it seems like the authors' intention was to have a response to every input that a bot has ever seen. The ANGie project strives to have intelligent and sensible responses, but to allow the bot to have no response when the meaning of the input is inconclusive, when additional context would be required to properly respond, or in general for questions for which the bot is unprepared - in order to create a bot that is capable of carrying on basic conversations with a human similar to the sort of small talk that two humans might have. Requires PyAIMLng, PyGOAPng, and aimlGOAP. -
23
Simple program for artificial neural network users. Right now the program can manipulate with Feed forward back propagation network.
-
24
Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
-
25
Agently
AI Agent Application Development Framework
Build AI agent native application in very little code. Easy to interact with AI agents in code using structure data and chained-calls syntax. Enhance AI Agent using plugins instead of rebuilding a whole new agent. Agently is a development framework that helps developers build AI agent native applications really fast. You can use and build AI agents in your code in an extremely simple way.
