incubator-xtable
autogen
| incubator-xtable | autogen | |
|---|---|---|
| 5 | 32 | |
| 695 | 25,821 | |
| 10.8% | 8.8% | |
| 9.3 | 9.9 | |
| 2 days ago | 2 days ago | |
| Java | Jupyter Notebook | |
| Apache License 2.0 | 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.
incubator-xtable
- FLaNK AI-April 22, 2024
- FLaNK AI Weekly 25 March 2025
- FLaNK Stack Weekly for 20 Nov 2023
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OneTable is now live | Table format interoperability is not a dream anymore
I'm excited to share that the project is now live and I wanted to thank the project's early contributors. You can learn more by visiting the repo: https://github.com/onetable-io/onetable
- Show HN: OneTable interop across Delta, Hudi, Iceberg
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?
email2phonenumber - A OSINT tool to obtain a target's phone number just by having his email address
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
doris - Apache Doris is an easy-to-use, high performance and unified analytics database.
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
starrocks - StarRocks, a Linux Foundation project, is a next-generation sub-second MPP OLAP database for full analytics scenarios, including multi-dimensional analytics, real-time analytics, and ad-hoc queries. InfoWorld’s 2023 BOSSIE Award for best open source software.
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
sql-cli-for-apache-flink-docker - SQL CLI for Apache Flink® via docker-compose
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.
connectors - This library allows Scala and Java-based projects (including Apache Flink, Apache Hive, Apache Beam, and PrestoDB) to read from and write to Delta Lake.
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
Local-Data-LakeHouse - Sample Data Lakehouse deployed in Docker containers using Apache Iceberg, Minio, Trino and a Hive Metastore. Can be used for local testing.
langchain - 🦜🔗 Build context-aware reasoning applications