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Top 23 Python agentic-ai Projects
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AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
AutoGPT (agpt.co): Open-source autonomous agent framework, released in 2023. Pioneering example of general-purpose agent architecture; known for demonstrating both promise and limitations of autonomous systems.
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ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
Project mention: I Scanned 5 Popular Open-Source AI Projects for EU AI Act Compliance. Here's What I Found. | dev.to | 2026-03-31I ran AIR Blackbox (the scanner itself), Browser Use (79K+ stars), RAGFlow (76K+ stars), LiteLLM (23K+ stars), and Superlinked (15K+ stars) through the same compliance checks.
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Birdclaw is interesting because it gives agents access to a Twitter archive. [17] GBrain points at a personal recall layer around OpenClaw / Hermes-style workflows. [18] PageIndex is a useful reminder that simple retrieval, even BM25-only retrieval, still has a place. [19] The “RAG comeback in about 8 months” take lands because the archive problem is still unsolved in practice. [20]
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agenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills. Enjoy an autonomous agent that thinks, browses the web, and code for the sole cost of electricity. đź”” Official updates only via twitter @Martin993886460 (Beware of fake account)
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adk-python
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Project mention: I Built an Autonomous AI Agent with Google ADK + Gemini 2.0 Flash That Spots Trends and Drafts Dev.to Articles for Me | dev.to | 2026-06-02Google ADK. (Check out the Google ADK Docs if you need help installing).
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Microsoft's agent-lightning project offers a comprehensive toolkit aimed at accelerating the process of building, testing, and deploying AI Agents. This open-source initiative highlights the industry's commitment to enabling faster development and implementation of advanced AI capabilities, providing developers with robust resources to streamline AI agent creation.
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claude-skills
337 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 330+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 more coding agents — engineering, marketing, product, compliance, C-level advisory, research, business operations, commercial & finance, and your daily productivity skills.
Project mention: Best Claude Code skills in 2026: the honest list (free and paid) | dev.to | 2026-05-30Free option just as valid: install from alirezarezvani/claude-skills and run the 7-check audit framework yourself.
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The memory interface shapes everything downstream. Committing to Hindsight's retain/recall abstraction early made the rest of the code straightforward. The LLM layer doesn't know where notes came from. The Flask layer doesn't know how retrieval works. Those boundaries are cheap at the start and expensive to add later.
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memU
The memory harness for proactive AI agents — structured storage, intent capture, 10x token reduction.
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agent-framework
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
Project mention: Microsoft Foundry Just Added CI/CD for AI Agents. Here's What That Actually Changes. | dev.to | 2026-05-25For teams already using Microsoft Agent Framework, the v1.0 release is now stable across Python and .NET, unifying the enterprise-grade foundations of Semantic Kernel with the multi-agent orchestration from AutoGen. It ships with native MCP, A2A, and OpenAPI support out of the box.
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git submodule add https://github.com/The-Pocket/PocketFlow.git vendor/pocketflow
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ART
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen3.6, GPT-OSS, Llama, and more!
Huh?
I thought the latest advance in computing (spring 2025) is self-play / reinforcement learning. Like we've ran out of training data a few years ago.
https://github.com/OpenPipe/ART
Reinforcement learning having the large language model devise puzzles that they solve via llm-as-judge.
The definition of llm-as-judge is your llm generate 8-12 trajectories and a different llm judges the result. I'd use an oracle like windows or linux operating system execution for the problem of ISA-assembly creation.
The winning entries are used to train the large language model.
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Vision-Agents
Open Vision Agents by Stream. Build voice and vision agents quickly with any model or video provider. Uses Stream's edge network for ultra-low latency.
You now have a voice participant that can sit in on a call, pull answers from your indexed docs, and speak them back with a face on the video. This is especially valuable for teammates who aren't deep in the codebase or may not be available due to timezone differences. It's exciting to see how agents like this are evolving to meet real-world use cases, and how frameworks such as Vision Agents make it straightforward to build and integrate these capabilities into your workflows.
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agent-squad
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
Project mention: Orchestrating Multi-Agents: Unifying Fragmented Tools into Coordinated Workflows | dev.to | 2025-06-29AWS Agent Squad (GitHub)
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Project mention: Your Agent Doesn't Need That 10,000-Token API Response: Context Offloading with Strands | dev.to | 2026-06-09
Strands Agents just shipped the ContextOffloader plugin. It's available in both the TypeScript and Python SDKs. It prevents large tool results from consuming your agent's context window automatically. When a tool returns a result that exceeds a configurable token threshold, the plugin stores each content block individually in an external storage backend and replaces it in the conversation with a truncated preview plus per-block references. Each offloaded result includes inline guidance telling the agent to use its available tools to selectively access the data it needs.
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mini-swe-agent
The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >74% on SWE-bench verified!
Project mention: I Built an AI Issue Triage Bot in 500 Lines of TypeScript — Here's How | dev.to | 2026-05-28Phase 3: Integration with mini-swe-agent for automated fix PRs
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Well, no ... For a start any "AI" course 20 years ago probably wouldn't have even mentioned neural nets, and certainly not as a mainstream technique.
A 20yr old "AI" curriculum would have looked more like the 3rd edition of Russel & Norvig's "Artificial Intelligence - A Modern Approach".
https://github.com/yanshengjia/ml-road/blob/master/resources...
Karpathy's videos aren't an AI (except in modern sense of AI=LLMs) course, or even a machine learning course, or even a neural network course for that matter (despite the title) - it's really just "From Zero to LLMs".
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solace-agent-mesh
An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.
Project mention: Ditch the Monolith: Build Scalable AI Teams with Solace Agent Mesh | dev.to | 2025-10-10View the Project on GitHub
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AG2 (formerly AutoGen) changes that. It provides a shared runtime where specialized agents with defined roles, tools and conversation patterns can collaborate as one coordinated team across models and even frameworks.
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Project mention: OptiLLM: Accuracy improvements on reasoning tasks with zero training | news.ycombinator.com | 2025-11-23
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Project mention: We audited LoCoMo: 6.4% of the answer key is wrong and the judge accepts up to 63% of intentionally | dev.to | 2026-04-04
There is also no standardized evaluation pipeline. Each system uses its own ingestion method (arguably necessary given architectural differences), its own answer generation prompt, and sometimes entirely different models. Scores are then compared in tables as if they share a common methodology. Multiple independent researchers have documented inability to reproduce published results (EverMemOS #73, Mem0 #3944, Zep scoring discrepancy).
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Project mention: II-Agent: a new open-source framework to build and deploy intelligent agents | news.ycombinator.com | 2025-11-07
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Python agentic-ai discussion
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A note from our sponsor - SaaSHub
www.saashub.com | 9 Jun 2026
Index
What are some of the best open-source agentic-ai projects in Python? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | AutoGPT | 184,738 |
| 2 | ragflow | 81,919 |
| 3 | PageIndex | 32,583 |
| 4 | agenticSeek | 26,450 |
| 5 | adk-python | 19,995 |
| 6 | agent-lightning | 17,276 |
| 7 | claude-skills | 17,158 |
| 8 | hindsight | 15,630 |
| 9 | memU | 13,785 |
| 10 | agent-framework | 11,058 |
| 11 | PocketFlow | 10,713 |
| 12 | ART | 9,893 |
| 13 | Vision-Agents | 7,897 |
| 14 | agent-squad | 7,646 |
| 15 | harness-sdk | 6,020 |
| 16 | mini-swe-agent | 4,967 |
| 17 | ml-road | 4,802 |
| 18 | solace-agent-mesh | 4,784 |
| 19 | ag2 | 4,638 |
| 20 | PPTAgent | 4,583 |
| 21 | optillm | 4,133 |
| 22 | EverOS | 3,563 |
| 23 | ii-agent | 3,347 |
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