hamilton
modelfusion
Our great sponsors
hamilton | modelfusion | |
---|---|---|
20 | 18 | |
1,312 | 896 | |
8.2% | 15.5% | |
9.8 | 9.9 | |
6 days ago | 3 days ago | |
Jupyter Notebook | TypeScript | |
BSD 3-clause Clear License | MIT License |
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.
hamilton
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Building an Email Assistant Application with Burr
Note that this uses simple OpenAI calls — you can replace this with Langchain, LlamaIndex, Hamilton (or something else) if you prefer more abstraction, and delegate to whatever LLM you like to use. And, you should probably use something a little more concrete (E.G. instructor) to guarantee output shape.
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Using IPython Jupyter Magic commands to improve the notebook experience
In this post, we’ll show how your team can turn any utility function(s) into reusable IPython Jupyter magics for a better notebook experience. As an example, we’ll use Hamilton, my open source library, to motivate the creation of a magic that facilitates better development ergonomics for using it. You needn’t know what Hamilton is to understand this post.
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FastUI: Build Better UIs Faster
We built an app with it -- https://blog.dagworks.io/p/building-a-lightweight-experiment. You can see the code here https://github.com/DAGWorks-Inc/hamilton/blob/main/hamilton/....
Usually we've been prototyping with streamlit, but found that at times to be clunky. FastUI still has rough edges, but we made it work for our lightweight app.
- Show HN: On Garbage Collection and Memory Optimization in Hamilton
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Facebook Prophet: library for generating forecasts from any time series data
This library is old news? Is there anything new that they've added that's noteworthy to take it for another spin?
[disclaimer I'm a maintainer of Hamilton] Otherwise FYI Prophet gels well with https://github.com/DAGWorks-Inc/hamilton for setting up your features and dataset for fitting & prediction[/disclaimer].
- Show HN: Declarative Spark Transformations with Hamilton
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Langchain Is Pointless
I had been hearing these pains from Langchain users for quite a while. Suffice to say I think:
1. too many layers of OO abstractions are a liability in production contexts. I'm biased, but a more functional approach is a better way to model what's going on. It's easier to test, wrap a function with concerns, and therefore reason about.
2. as fast as the field is moving, the layers of abstractions actually hurt your ability to customize without really diving into the details of the framework, or requiring you to step outside it -- in which case, why use it?
Otherwise I definitely love the small amount of code you need to write to get an LLM application up with Langchain. However you read code more often than you write it, in which case this brevity is a trade-off. Would you prefer to reduce your time debugging a production outage? or building the application? There's no right answer, other than "it depends".
To that end - we've come up with a post showing how one might use Hamilton (https://github.com/dagWorks-Inc/hamilton) to easily create a workflow to ingest data into a vector database that I think has a great production story. https://open.substack.com/pub/dagworks/p/building-a-maintain...
Note: Hamilton can cover your MLOps as well as LLMOps needs; you'll invariably be connecting LLM applications with traditional data/ML pipelines because LLMs don't solve everything -- but that's a post for another day.
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Free access to beta product I'm building that I'd love feedback on
This is me. I drive an open source library Hamilton that people doing time-series/ML work love to use. I'm building a paid product around it at DAGWorks, and I'm after feedback on our current version. Can I entice anyone to:
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IPyflow: Reactive Python Notebooks in Jupyter(Lab)
From a nuts and bolts perspective, I've been thinking of building some reactivity on top of https://github.com/dagworks-inc/hamilton (author here) that could get at this. (If you have a use case that could be documented, I'd appreciate it.)
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Data lineage
Most people don't track lineage because it's difficult (though if you use something like https://github.com/DAGWorks-Inc/hamilton to write your pipeline - author here - it can come almost for free).
modelfusion
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Next.js and GPT-4: A Guide to Streaming Generated Content as UI Components
ModelFusion is an AI integration library that I am developing. It enables you to integrate AI models into your JavaScript and TypeScript applications. You can install it with the following command:
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Effortlessly Generate Structured Information with Ollama, Zod, and ModelFusion
ModelFusion is an open-source library I'm developing to integrate AI models seamlessly into TypeScript projects. It provides an Ollama client and a generateStructure function.
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Create Your Own Local Chatbot with Next.js, Ollama, and ModelFusion
ModelFusion: ModelFusion is a library for building multi-modal AI applications that I've been working on. It provides a streamText function that calls AI models and returns a streaming response. ModelFusion also contains an Ollama integration that we will use to access the OpenHermes 2.5 Mistral model.
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PDF Chat with Node.js, OpenAI and ModelFusion
You can find the complete code for the chatbot here: github/com/lgrammel/modelfusion/examples/pdf-chat-terminal
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Ask HN: Tell us about your project that's not done yet but you want feedback on
I’m working on ModelFusion, a TypeScript library for working with AI models (llm, image, etc.)
https://github.com/lgrammel/modelfusion
It is only getting limited traction so I’m wondering if I’m missing something fundamental with the approach that I’m taking.
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LangChain Agent Simulation – Multi-Player Dungeons and Dragons
If you work with JS or TS, check out this alternative that I've been working on:
https://github.com/lgrammel/modelfusion
It lets you stay in full control over the prompts and control flow while make a lot of things easier and more convenient.
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Introducing ModelFusion: Build AI apps with JavaScript and TypeScript.
The response also contains additional information such as the metadata and the full response. The ModelFusion documentation contains many examples and demo apps.
- Show HN: AI-utils.js – TypeScript-first lib for AI apps, chatbots, and agents
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ai-utils.js VS langchainjs - a user suggested alternative
2 projects | 26 Jul 2023
- ai-utils.js: TypeScript-first library for building AI apps, chatbots, and agents.
What are some alternatives?
dagster - An orchestration platform for the development, production, and observation of data assets.
langroid - Harness LLMs with Multi-Agent Programming
tree-of-thought-llm - [NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
langchainjs - 🦜🔗 Build context-aware reasoning applications 🦜🔗
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.
aipl - Array-Inspired Pipeline Language
snowpark-python - Snowflake Snowpark Python API
async-interval-job - ✨ setInterval for promises and async/sync functions. Support graceful shutdown and prevent multiple executions from overlapping in time.
chatflow - Leveraging LLM to build Conversational UIs
vscode-reactive-jupyter - A simple Reactive Python Extension for Visual Studio Code
meta-parser - Universal meta-tag scrapper for Node.js. Works both with CJS and ESM modules.