garnet
autogen
| garnet | autogen | |
|---|---|---|
| 4 | 32 | |
| 9,326 | 25,506 | |
| 26.8% | 7.7% | |
| 9.3 | 9.9 | |
| 4 days ago | 3 days ago | |
| C# | Jupyter Notebook | |
| MIT License | 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.
garnet
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A MySQL compatible database engine written in pure Go
You would be surprised by performance of modern .NET :)
Writing no-alloc is oftentimes done by reducing complexity and not doing "stupid" tricks that actually work against JIT and CoreLib features.
For databases specifically, .NET is actually positioned very well with its low-level features (intrisics incl. SIMD, FFI, struct generics though not entirely low-level) and high-throughput GC.
Interesting example of this applied in practice is Garnet[0]/FASTER[1]. Keep in mind that its codebase still consist of un-idiomatic C# and you can do way better by further simplification, but it already does the job well enough.
[0] https://github.com/microsoft/garnet
[1] https://github.com/microsoft/FASTER
- FLaNK AI Weekly 25 March 2025
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Redis License Changed
At the same time Microsoft releases Garnet: https://github.com/microsoft/garnet
Good timing.
- Garnet – A new remote cache-store from Microsoft Research
autogen
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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
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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
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AutoGen v0.2.2 released
New example notebook demoing video transcript translate with whisper.
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AutoGen v0.2.1 released
New release: v0.2.1
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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.
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Our Hacktoberfest Success Story
Microsoft autogen
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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
What are some alternatives?
redis - Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
KeyDB - A Multithreaded Fork of Redis
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
FASTER - Fast persistent recoverable log and key-value store + cache, in C# and C++.
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
dragonfly - A modern replacement for Redis and Memcached
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.
FLiPStackWeekly - FLaNK AI Weekly covering Apache NiFi, Apache Flink, Apache Kafka, Apache Spark, Apache Iceberg, Apache Ozone, Apache Pulsar, and more...
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
deeplake - Database for AI. Store Vectors, Images, Texts, Videos, etc. Use with LLMs/LangChain. Store, query, version, & visualize any AI data. Stream data in real-time to PyTorch/TensorFlow. https://activeloop.ai
langchain - 🦜🔗 Build context-aware reasoning applications