Open Source Python Agentic AI Tools
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Python Agentic AI Tools
View 95 business solutionsBrowse free open source Python Agentic AI Tools and projects below. Use the toggles on the left to filter open source Python Agentic AI Tools by OS, license, language, programming language, and project status.
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DAT Freight and Analytics - DATDAT Freight & Analytics operates DAT One, North America’s largest truckload freight marketplace; DAT iQ, the industry’s leading freight data analytics service; and Trucker Tools, the leader in load visibility. Shippers, transportation brokers, carriers, news organizations, and industry analysts rely on DAT for market trends and data insights, informed by nearly 700,000 daily load posts and a database exceeding $1 trillion in freight market transactions. Founded in 1978, DAT is a business unit of Roper Technologies (Nasdaq: ROP), a constituent of the Nasdaq 100, S&P 500, and Fortune 1000. Headquartered in Beaverton, Ore., DAT continues to set the standard for innovation in the trucking and logistics industry.
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Agent Zero
Agent Zero AI framework
Agent Zero is not a predefined agentic framework. It is designed to be dynamic, organically growing, and learning as you use it. Agent Zero is fully transparent, readable, comprehensible, customizable and interactive. Agent Zero uses the computer as a tool to accomplish its (your) tasks. Agents can communicate with their superiors and subordinates, asking questions, giving instructions, and providing guidance. Instruct your agents in the system prompt on how to communicate effectively. The terminal interface is real-time streamed and interactive. You can stop and intervene at any point. If you see your agent heading in the wrong direction, just stop and tell it right away. There is a lot of freedom in this framework. You can instruct your agents to regularly report back to superiors asking for permission to continue. You can instruct them to use point-scoring systems when deciding when to delegate subtasks. Superiors can double-check subordinates' results and disputes. -
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Magentic UI
A research prototype of a human-centered web agent
Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight. -
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OpenAI Python
The official Python library for the OpenAI API
The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx. -
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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. -
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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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FastAgency
The fastest way to bring multi-agent workflows to production
FastAgency is a framework that simplifies the creation and deployment of AI-driven automation agents. It provides a structured environment for developing AI assistants capable of handling various business and technical tasks. -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher accuracy and 83%+ success on complex workflows. Developers can integrate via Python/TypeScript SDKs or REST API, with support for OpenAI, Claude, Gemini, LangChain, LlamaIndex, and CrewAI. Features include built-in authentication, multi-tenancy, hosted servers, Docker support, and enterprise security guardrails. Licensed under Apache 2.0, Klavis simplifies AI development by eliminating complex authentication management and enabling seamless workflow automation across multiple applications. -
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Agent S2
Agent S: an open agentic framework that uses computers like a human
Simular's Agent S2 represents a leap forward in the development of computer-use agents, capable of autonomously interacting with a range of devices and interfaces. By integrating specialized AI models, Agent S2 delivers state-of-the-art performance, whether on desktop systems or smartphones. Through modular architecture, it efficiently handles complex tasks, such as navigating UIs, performing low-level actions like text selection, and executing high-level strategies like planning. Additionally, the system's proactive hierarchical planning allows for real-time adaptation, making it an ideal solution for businesses seeking to streamline operations and automate digital workflows. Agent S2 is designed with flexibility, enabling seamless scaling for future applications and tasks. -
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise. -
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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. -
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Browser Use
Make websites accessible for AI agents
Browser-Use is a framework that makes websites accessible for AI agents, enabling automated interactions and data extraction from web pages. -
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DSPy
DSPy: The framework for programming—not prompting—language models
Developed by the Stanford NLP Group, DSPy (Declarative Self-improving Python) is a framework that enables developers to program language models through compositional Python code rather than relying solely on prompt engineering. It facilitates the construction of modular AI systems and provides algorithms for optimizing prompts and weights, enhancing the quality and reliability of language model outputs. -
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OpenAGI
When LLM Meets Domain Experts
OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. The project includes tooling for registering agents with AIOS by uploading them via a command-line interface, enforcing a consistent naming scheme that matches the local folder layout. A companion tooling layer lets agents call external tools described in the tools.md documentation, enabling them to orchestrate APIs, retrieval pipelines, and other utilities in response to LLM decisions. -
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Haystack
Haystack is an open source NLP framework to interact with your data
Apply the latest NLP technology to your own data with the use of Haystack's pipeline architecture. Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning, not just keywords! Make use of and compare the latest pre-trained transformer-based languages models like OpenAI’s GPT-3, BERT, RoBERTa, DPR, and more. Pick any Transformer model from Hugging Face's Model Hub, experiment, find the one that works. Use Haystack NLP components on top of Elasticsearch, OpenSearch, or plain SQL. Boost search performance with Pinecone, Milvus, FAISS, or Weaviate vector databases, and dense passage retrieval. -
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AgentRun
The easiest, and fastest way to run AI-generated Python code safely
AgentRun is a framework for building autonomous AI agents capable of executing complex tasks with minimal human intervention. It provides a structured environment for defining agent behaviors, managing workflows, and integrating AI models to achieve specific goals. -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous cooperation, we propose a novel communicative agent framework named role-playing. Our approach involves using inception prompting to guide chat agents toward task completion while maintaining consistency with human intentions. We showcase how role-playing can be used to generate conversational data for studying the behaviors and capabilities of chat agents, providing a valuable resource for investigating conversational language models. -
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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. -
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Qwen-Agent
Agent framework and applications built upon Qwen>=3.0
Qwen-Agent is a framework for building applications / agents using Qwen models (version 3.0+). It provides components for instruction following, tool usage (function calling), planning, memory, RAG (retrieval augmented generation), code interpreter, etc. It ships with example applications (Browser Assistant, Code Interpreter, Custom Assistant), supports GUI front-ends, backends, server setups. Agent workflow can maintain context / memory to perform multi-turn or more complex logic over time. It acts as the backend for Qwen Chat among other use cases. Built-in Code Interpreter tool that can execute code (locally) as part of agent workflows. -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
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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. -
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AppWorld
World of apps for benchmarking interactive coding agent
AppWorld is a framework developed by Stony Brook University's NLP group to simulate environments for training and evaluating dialogue agents in task-oriented applications. -
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AskUI Vision Agent
Enable AI to control your desktop, mobile and HMI devices
AskUI’s Vision Agent is an automation framework that allows you—and AI agents—to control real desktops, mobile devices, and HMI systems by perceiving the UI and performing actions like clicking, typing, scrolling, and drag-and-drop. It is designed for multi-platform compatibility and supports multiple AI models so you can tailor perception and decision-making to your workload. The repository presents a feature overview, sample media, and frequent release notes, which show ongoing improvements such as CORS checks and other operational tweaks. The broader AskUI documentation covers the Python Vision Agent along with suite services and inference APIs, indicating a productized ecosystem rather than a single library. Community-curated lists also recognize Vision Agent as part of the broader “GUI agents” landscape, placing it among other computer-use agents. -
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Cybergod
A program that can do anything to earn money without human operators
AGI Computer Control is an experimental autonomous software system designed to operate independently and generate income without human intervention. 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. -
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DB-GPT
Revolutionizing Database Interactions with Private LLM Technology
DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. -
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GPTme
Your agent in your terminal, equipped with local tools
GPTMe is a personal AI chatbot designed for self-reflection, journaling, and productivity, using GPT models to generate personalized insights and responses.
