autogen
awesome-ai-agents
autogen | awesome-ai-agents | |
---|---|---|
32 | 16 | |
25,506 | 6,903 | |
7.7% | 19.3% | |
9.9 | 9.3 | |
4 days ago | 5 days ago | |
Jupyter Notebook | ||
Creative Commons Attribution 4.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
autogen
-
Agents of Change: Navigating the Rise of AI Agents in 2024
AutoGen is an AI framework by Microsoft designed to streamline multi-agent conversations. AutoGen allows agents to communicate, share information, and make collective decisions. This setup enhances the responsiveness and dynamism of conversations. Developers use AutoGen to tailor agents to specific roles, such as programmer, content writer, CEO, etc. This enhances their ability to handle tasks from simple queries to intricate problem-solving.
- FLaNK AI Weekly 25 March 2025
-
Launch HN: Glide (YC W19) – AI-assisted technical design docs
I am still playing around with the project but FYI, the parsing for the github repo URL at https://glide.agenticlabs.com/ will fail if there's a trailing slash in the repo link i.e. https://github.com/microsoft/autogen/ won't work but https://github.com/microsoft/autogen will.
- Show HN: Prompts as (WASM) Programs
- Enable Next-Gen Large Language
-
AutoGen v0.2.2 released
New example notebook demoing video transcript translate with whisper.
-
AutoGen v0.2.1 released
New release: v0.2.1
-
AI is making us all more productive — but in a weird and unexpected way
I disagree with the conclusion. In software, I've seen 10x engineers in person and I don't think they're replaceable. Whereas, the new college grad or that entry level dev who doesn't design anything and just writes small amounts of code, doing exactly as told is replaceable by an AI. Frameworks similar to Microsoft Autogen(https://github.com/microsoft/autogen) can in theory build agents who can do these tasks with ease whereas a 10x engineer can focus on directing the agents and designing systems.
-
Our Hacktoberfest Success Story
Microsoft autogen
-
AutoGen v0.2.0b4 released
CompressibleAgent (experimental) can be used to handle long conversations. Notebook: https://github.com/microsoft/autogen/blob/main/notebook/agentchat_compression.ipynb
awesome-ai-agents
- Open-source secure sandboxes for AI code execution
-
Llama 3 with Function Calling and Code Interpreter
# TODO: Get your Groq AI API key from https://console.groq.com/ GROQ_API_KEY = "" # TODO: Get your E2B API key from https://e2b.dev/docs E2B_API_KEY = "" # Or use 8b version # MODEL_NAME = "llama3-8b-8192" MODEL_NAME = "llama3-70b-8192" SYSTEM_PROMPT = """you are a python data scientist. you are given tasks to complete and you run python code to solve them. - the python code runs in jupyter notebook. - every time you call `execute_python` tool, the python code is executed in a separate cell. it's okay to multiple calls to `execute_python`. - display visualizations using matplotlib or any other visualization library directly in the notebook. don't worry about saving the visualizations to a file. - you have access to the internet and can make api requests. - you also have access to the filesystem and can read/write files. - you can install any pip package (if it exists) if you need to but the usual packages for data analysis are already preinstalled. - you can run any python code you want, everything is running in a secure sandbox environment""" tools = [ { "type": "function", "function": { "name": "execute_python", "description": "Execute python code in a Jupyter notebook cell and returns any result, stdout, stderr, display_data, and error.", "parameters": { "type": "object", "properties": { "code": { "type": "string", "description": "The python code to execute in a single cell.", } }, "required": ["code"], }, }, } ]
-
Show HN: Open-source SDK for creating custom code interpreters with any LLM
Hey everyone! I'm the CEO of the company that built this SDK.
We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2].
You can think of us as giving small cloud computers to LLMs.
We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense
The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4].
We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software. We work with any LLM. Here's how we added code interpreter to the new Llama-3 models [5].
Our long-term plan is to build an automated AWS for AI apps and agents.
Happy to answer any questions and hear feedback!
[0] https://e2b.dev/
[1] https://github.com/e2b-dev
[2] https://github.com/firecracker-microvm/firecracker
[3] https://e2b.dev/docs
[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...
[5] https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/l...
- List of open-source AI assistants
- List of AI Agents
-
Overview: AI Assembly Architectures
github.com/awesome-ai-agents
-
List of Awesome AI Agents like AutoGPT and BabyAGI / Many open-source Agents with code included!
Github: https://github.com/e2b-dev/awesome-ai-agents and https://github.com/EmbraceAGI/Awesome-AGI
- Show HN: A list of open-source AI agents
- We're building a list of open-source AI agents. How has been your experience with them?
- We made a comprehensive list of popular AI agents out there
What are some alternatives?
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
AgentVerse - 🤖 AgentVerse 🪐 is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
bondai
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.
EdgeChains - EdgeChains.js Typescript/Javascript production-friendly Generative AI. Based on Jsonnet. Works anywhere that Webassembly does. Prompts live declaratively & "outside code in config". Kubernetes & edge friendly. Compatible with OpenAI GPT, Gemini, Llama2, Anthropic, Mistral and others
malmo - Project Malmo is a platform for Artificial Intelligence experimentation and research built on top of Minecraft. We aim to inspire a new generation of research into challenging new problems presented by this unique environment. --- For installation instructions, scroll down to *Getting Started* below, or visit the project page for more information:
langchain - 🦜🔗 Build context-aware reasoning applications
babyagi-asi - BabyAGI: an Autonomous and Self-Improving agent, or BASI