autogen
haystack
| autogen | haystack | |
|---|---|---|
| 32 | 55 | |
| 25,506 | 13,784 | |
| 7.7% | 3.6% | |
| 9.9 | 9.9 | |
| 3 days ago | about 20 hours ago | |
| Jupyter Notebook | Python | |
| Creative Commons Attribution 4.0 | Apache License 2.0 |
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
haystack
-
Haystack DB – 10x faster than FAISS with binary embeddings by default
I was confused for a bit but there is no relation to https://haystack.deepset.ai/
-
Release Radar • March 2024 Edition
View on GitHub
-
First 15 Open Source Advent projects
4. Haystack by Deepset | Github | tutorial
-
Generative AI Frameworks and Tools Every Developer Should Know!
Haystack can be classified as an end-to-end framework for building applications powered by various NLP technologies, including but not limited to generative AI. While it doesn't directly focus on building generative models from scratch, it provides a robust platform for:
-
Best way to programmatically extract data from a set of .pdf files?
But if you want an API that you can use to develop your own flow, Haystack from Deepset could be worth a look.
-
Which LLM framework(s) do you use in production and why?
Haystack for production. We cannot afford breaking changes in our production apps. Its stable, documentation is excellent and did I mention its' STABLE!??
- Overview: AI Assembly Architectures
-
Llama2 and Haystack on Colab
I recently conducted some experiments with Llama2 and Haystack (https://github.com/deepset-ai/haystack), the NLP/LLM framework.
The notebook can be helpful for those trying to load Llama2 on Colab.
1) Installed Transformers from the main branch (and other libraries)
- Build with LLMs for production with Haystack – has 10k stars on GitHub
- Show HN: Haystack – Production-Ready LLM Framework
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]
langchain - 🦜🔗 Build context-aware reasoning applications
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
gpt-neo - An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
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
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
langroid - Harness LLMs with Multi-Agent Programming
jina - ☁️ Build multimodal AI applications with cloud-native stack