EdgeChains
autogen
EdgeChains | autogen | |
---|---|---|
12 | 32 | |
289 | 25,506 | |
4.8% | 7.7% | |
9.4 | 9.9 | |
4 days ago | 4 days ago | |
JavaScript | Jupyter Notebook | |
MIT License | Creative Commons Attribution 4.0 |
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EdgeChains
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HonoJS: Small, simple, and ultrafast web framework for the Edges
We build a WASM compiler to compile our prompts and chains into webassembly. Honojs was a critical part of it.
https://github.com/arakoodev/EdgeChains/
- looking for someone to codereview an opensource Typescript+webassembly framework for Generative AI apps
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Overview: AI Assembly Architectures
EdgeChains: github.com/arakoodev/EdgeChains
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Stanford DSPy: The framework for programming with foundation models
would love your thoughts on this as well - https://github.com/arakoodev/edgechains
got frustrated in the same way with "Black Box Prompting - every library hides prompts/chains in layers of libraries...while it should have been declarative.
EdgeChains - allows u to specify ur prompt and chain in jsonnet. This why i think Generative AI needs declarative orchestration and not previous generations. https://github.com/arakoodev/edgechains#why-do-you-need-decl...
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Show HN: Chat with your data using LangChain, Pinecone, and Airbyte
when will you have pgvector as a destination ? we (https://github.com/arakoodev/edgechains) work with a lot of enterprises and they would not move away from using redis or pgvector even as their vector store. Is there a way where we can leverage that ?
Second, for a LOT of enterprises, they want to use non-openai embedding models (minilm, GTE, BGE), will you support that. For e.g. in Edgechains we natively support BGE and minilm. Would you be able to support that ?
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Chunking 2M+ files a day for Code Search using Syntax Trees
oh really ? Thats awfully kind. I'll take that in for EdgeChains as well.
https://github.com/arakoodev/EdgeChains/issues/172
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Langchain Is Pointless
Promptfile is written in markdown, which is unsuited for templates and config management.
I have an attempt in the same domain, would love feedback
We didnt invent a new markup - we used jsonnet which is used in large scale kubernetes and has a grammar that has been well tested for config mgmt.
https://github.com/arakoodev/EdgeChains/blob/main/Examples/r...
Prompts live outside the code.
- Calling ChatGPT API from Spring Boot
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?
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/AutoGPT]
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
semantic-kernel - Integrate cutting-edge LLM technology quickly and easily into your apps
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
SuperAGI - <⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
awesome-ai-agents - A list of AI autonomous agents
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.
langchain - 🦜🔗 Build context-aware reasoning applications
dspy - DSPy: The framework for programming—not prompting—foundation models