Open Source Python AI Agents
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Python AI Agents
View 1017 business solutionsBrowse free open source Python AI Agents and projects below. Use the toggles on the left to filter open source Python AI Agents by OS, license, language, programming language, and project status.
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Agent Reach
Give your AI agent eyes to see the entire internet
Agent Reach is a command-line tool that gives AI agents access to public internet content across multiple platforms. It is designed for agent workflows that need to read and search sources like Twitter, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu without relying on paid platform APIs. The project focuses on giving AI tools broader visibility into social, video, code, and community data through one interface. It can be useful for research agents, automation workflows, competitive monitoring, content analysis, and social listening. Agent-Reach also supports modern agent environments by exposing capabilities that can be connected into larger AI workflows. Its main value is making scattered web platforms easier for agents to query, inspect, and summarize from the command line. -
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OpenSquilla
Token-Efficient AI Agent with same budget, higher intelligence density
OpenSquilla is a token-efficient microkernel AI agent runtime designed for CLI, web UI, and chat-based workflows. It routes each turn through a shared loop that can select lower-cost models when appropriate while preserving tool dispatch, retries, memory, and decision logging. The project supports multiple LLM providers through a pluggable provider layer, making it adaptable to different model ecosystems. It includes persistent memory, built-in web search, on-device embeddings, and sandboxing for safer execution. OpenSquilla is designed for users who want stronger agent capabilities without wasting tokens on every interaction. Its main value is combining cost-aware routing, durable context, and multi-channel agent execution in one local runtime. -
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OpenJarvis
Personal AI, On Personal Devices
OpenJarvis is an open-source framework designed to build personal AI agents that run primarily on local devices rather than relying on cloud infrastructure. Developed as part of the Intelligence Per Watt research initiative, it focuses on improving the efficiency and practicality of on-device AI systems. The framework provides shared primitives for building local-first agents, along with evaluation tools that measure performance using metrics such as energy consumption, latency, cost, and accuracy. OpenJarvis integrates with local inference engines like Ollama, vLLM, SGLang, and llama.cpp to run language models directly on personal hardware. It also includes a learning loop that allows models to improve over time using locally generated interaction traces. By prioritizing local execution and efficiency, OpenJarvis aims to provide a foundation for privacy-preserving personal AI assistants. -
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QwenPaw
A personal AI assistant, easy to install
QwenPaw is an AI agent framework developed by the AgentScope ecosystem to provide a desktop-style intelligent assistant powered by Qwen language models and modular agent orchestration. The project combines conversational AI, memory systems, tool usage, workflow automation, and multimodal interaction into a unified assistant environment designed for daily productivity and experimentation. It supports structured reasoning, autonomous task execution, and integration with external tools and APIs, allowing the assistant to perform actions beyond standard chatbot conversations. QwenPaw emphasizes extensibility through modular components that developers can customize for research, personal assistants, automation systems, or enterprise AI workflows. The architecture integrates agent collaboration, planning systems, and long-term contextual memory to create more persistent and adaptive interactions. -
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OpenManus
Open-source AI agent framework
OpenManus is an open-source AI agent framework designed to autonomously execute complex, multi-step tasks by combining reasoning, planning, and tool use. It enables developers to build agents that can think, act, and iterate toward goals rather than simply responding to prompts. The platform emphasizes task decomposition, allowing agents to break down objectives into smaller steps and execute them sequentially or recursively. OpenManus supports integration with external tools, APIs, and environments, making it suitable for real-world automation workflows. It is built to be flexible and extensible, enabling customization of agent behaviors, tools, and reasoning strategies. Overall, OpenManus provides a foundation for creating more capable, autonomous AI systems that can handle dynamic and goal-driven tasks. -
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OpenHands
Open-source autonomous AI software engineer
Welcome to OpenHands (formerly OpenDevin), an open-source autonomous AI software engineer who is capable of executing complex engineering tasks and collaborating actively with users on software development projects. Use AI to tackle the toil in your backlog, so you can focus on what matters: hard problems, creative challenges, and over-engineering your dotfiles We believe agentic technology is too important to be controlled by a few corporations. So we're building all our agents in the open on GitHub, under the MIT license. Our agents can do anything a human developer can: they write code, run commands, and use the web. We're partnering with AI safety experts like Invariant Labs to balance innovation with security. -
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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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GenericAgent
Self-evolving autonomous agent framework
The GenericAgent project is a flexible framework for building autonomous AI agents that can operate across diverse tasks and environments. It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation. It integrates with modern language models to provide planning, execution, and iterative reasoning capabilities, making it suitable for complex workflows. The project also focuses on extensibility, allowing developers to plug in custom tools or APIs and tailor agent behavior to specific use cases. By abstracting common agent patterns, it reduces the overhead of building agent systems from scratch. Overall, GenericAgent provides a foundation for scalable and reusable AI agent development. -
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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. -
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Oh My Hermes
All in one plugin for Hermes Agent
Oh My Hermes is an operating layer for Hermes Agent that adds structured routing, coding workflows, long-term memory, and evidence-aware execution. It keeps Hermes as the conversational front end while deciding which workflow, model category, and specialist capability should handle each task. Work can be split into parallel lanes with isolated worktrees and typed completion states. The plugin includes a reviewed memory system that stores approved records with provenance and aging rules. Its terminal interface shows delegated lanes, models, effort, cost, progress, and verification status. It also provides more than 100 specialist skills spanning coding, design, debugging, security, performance, and refactoring. Model chains remain user-editable and can fall back across providers when a preferred route is unavailable. -
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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. -
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Browser Use
Make websites accessible for AI agents
Browser Use is an AI-powered browser automation framework designed to let agents interact with websites just like humans do. It enables developers and AI systems to perform complex online tasks such as form filling, data extraction, and navigation through natural language instructions. Built with Python and compatible with modern LLMs, it integrates seamlessly with tools like ChatBrowserUse, Google Gemini, and Anthropic models. The platform supports both open-source deployment and a fully hosted cloud version for enhanced scalability and performance. Its cloud offering includes advanced capabilities like stealth browsing, CAPTCHA solving, and proxy rotation for reliable automation. Overall, Browser Use transforms web interaction into an intelligent, programmable workflow driven by AI agents. -
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Thoth
Thoth - Personal AI Sovereignty. A local-first AI assistant
Thoth is an AI-driven system designed to support advanced reasoning, knowledge processing, or agentic workflows, likely inspired by the concept of structured intelligence and decision-making. It focuses on organizing and synthesizing information in a way that enables deeper insights and more autonomous behavior. The project may incorporate LLMs, data pipelines, and modular components to handle complex tasks such as reasoning, planning, or knowledge retrieval. Its architecture likely emphasizes extensibility, allowing developers to customize workflows or integrate external tools. Thoth appears to target users interested in building intelligent systems that go beyond simple prompt-response interactions. It reflects a broader trend toward agent-based, reasoning-capable AI systems. -
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ChatArena
ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments
ChatArena is a library that provides multi-agent language game environments and facilitates research about autonomous LLM agents and their social interactions. -
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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. The agent interfaces with messaging platforms like Telegram, Discord, Slack, and WhatsApp through a single gateway process, and also offers an interactive terminal user interface with history, autocomplete, and streamable tool output. It supports scheduled automation in natural language, allowing users to set up recurring tasks such as daily briefings or system audits that it runs unattended. -
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Sinas
Open-source platform for building AI applications
Sinas is an open-source platform for building AI applications without handing over your data. It sits between your applications and the LLM models, bringing AI agents, Python functions, database queries, state, files and permissions together behind one API, in an instance that belongs to you. Sinas runs in two ways on the same AGPL v3 code. Sinas Cloud is a managed service with upgrades, monitoring and backups handled for you, and a free plan that needs no credit card. Self-hosted, it runs on any Linux server or Kubernetes cluster. AI agents work with OpenAI, Anthropic, Mistral or local models via Ollama, with tool calling, streaming and agent-to-agent orchestration. Python functions run in isolated containers, triggered by agents, APIs, webhooks or schedules. SQL templates connect to PostgreSQL, ClickHouse and Snowflake. Access control, OTP login, API keys and request logging are built in, and configuration can be exported to move between Cloud and self-hosting. -
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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. -
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Agentic Security
Agentic LLM Vulnerability Scanner / AI red teaming kit
The open-source Agentic LLM Vulnerability Scanner. -
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OpenHarness
Open Agent Harness with a built-in personal agent, Ohmo
OpenHarness is an open-source framework developed to support large-scale machine learning workflows, particularly in the context of training, evaluating, and benchmarking AI models. It provides a structured environment for orchestrating experiments, managing datasets, and standardizing evaluation processes across different models. The project focuses on reproducibility and scalability, allowing researchers and engineers to run consistent experiments while tracking results effectively. It often includes modular components that can be adapted to different machine learning pipelines, enabling flexibility across use cases such as recommendation systems, natural language processing, or multimodal tasks. OpenHarness is designed to integrate with modern ML ecosystems, supporting distributed training and efficient resource utilization. It also emphasizes collaboration, enabling teams to share configurations and results in a standardized format. -
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Bindu
Bindu: Turn any AI agent into a living microservice
Bindu is an open-source infrastructure layer that transforms any AI agent into a production-ready microservice capable of interacting, communicating, and transacting within a broader network of agents. It abstracts away the complexity of deployment, authentication, communication protocols, and payment systems by allowing developers to “bindufy” an agent with minimal configuration. Once integrated, the agent gains a decentralized identity, standardized communication capabilities through protocols such as A2A and AP2, and built-in support for authentication and monetization. The system is designed to be framework-agnostic, meaning developers can build agents using tools like LangChain, OpenAI SDK, or custom implementations and still deploy them seamlessly. Bindu also introduces the concept of an “Internet of Agents,” where multiple specialized agents collaborate, discover each other, and exchange services autonomously. -
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Scientific Agent Skills
A set of ready to use Agent Skills for research, science, engineering
Scientific Agent Skills is an open-source collection of ready-to-use agent skills designed to turn AI coding assistants into stronger research, science, engineering, and analysis partners. It supports any AI agent compatible with the Agent Skills standard, including tools such as Cursor, Claude Code, Codex, and Gemini CLI. The repository includes 135 skills across scientific domains such as genomics, cheminformatics, clinical research, medical imaging, machine learning, physics, materials science, geospatial analysis, and scientific writing. Each skill provides curated documentation, examples, best practices, and integration guidance so agents can execute complex workflows more reliably. It is especially useful for researchers who need AI assistance with databases, Python libraries, literature review, data analysis, and scientific communication. The project also emphasizes extensibility, security review, and practical installation through npx or GitHub CLI. -
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Eigent
The Open Source Cowork Desktop to Unlock Your Exceptional Productivity
Eigent is an open-source cowork desktop application designed to help you build, manage, and deploy a custom AI workforce. It enables multiple specialized AI agents to collaborate in parallel, turning complex workflows into automated, end-to-end tasks. Built on the CAMEL-AI multi-agent framework, Eigent emphasizes productivity, flexibility, and transparent system design. You can run Eigent fully locally for maximum privacy and data control, or choose a cloud-connected experience for quick access. The platform supports a wide range of AI models and integrates powerful tools through the Model Context Protocol (MCP). With human-in-the-loop controls and enterprise-ready features, Eigent balances automation with oversight and security. -
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OpenSRE
Build your own AI SRE agents. The open source toolkit for the AI era
OpenSRE is an open-source framework designed to build AI-powered Site Reliability Engineering agents that automate incident investigation and root cause analysis across modern cloud environments. It connects to observability tools, infrastructure systems, and communication platforms to gather logs, metrics, and traces in real time. When an alert is triggered, the system autonomously analyzes correlated signals, identifies anomalies, and generates structured investigation reports with probable causes and recommended actions. Its multi-agent architecture allows parallel reasoning across systems, mimicking how experienced SRE teams debug complex issues. The platform also incorporates memory and knowledge graph capabilities to learn from past incidents and improve future investigations. It is designed to run locally within an organization’s infrastructure, ensuring data privacy and compliance. -
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Academic Research Skills for Claude Code
Academic Research Skills for Claude Code
Academic Research Skills is a structured learning repository aimed at improving users’ ability to conduct rigorous academic research, particularly in technical and scientific domains. It compiles methodologies, frameworks, and best practices for literature review, critical analysis, and research writing. The project is designed as a self-guided resource, helping learners understand how to evaluate sources, synthesize information, and develop strong arguments. It likely integrates examples, templates, and conceptual explanations to bridge the gap between theory and practical research execution. The repository emphasizes skill-building rather than automation, making it especially useful for students and early-career researchers. Its overall goal is to enhance research literacy and reproducibility in academic workflows. -
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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.
