aipl
langstream
aipl | langstream | |
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4 | 4 | |
119 | 389 | |
- | - | |
9.2 | 8.7 | |
6 months ago | 4 months ago | |
Python | Python | |
MIT License | MIT License |
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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.
aipl
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Ask HN: Tell us about your project that's not done yet but you want feedback on
AIPL is an "Array-Inspired Pipeline Language", a tiny DSL in Python to make it easier to explore and experiment with AI pipelines.
https://github.com/saulpw/aipl
When you want to run some prompts through an LLM over a dataset, with some preprocessing and/or chaining prompts together, AIPL makes it much easier than writing a Python script.
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The Problem with LangChain
Yes! This is why I started working on AIPL. The scripts are much more like recipes (linear, contained in a single-file, self-evident even to people who don't know the language). For instance, here's a multi-level summarizer of a webpage: https://github.com/saulpw/aipl/blob/develop/examples/summari...
The goal is to capture all that knowledge that langchain has, into consistent legos that you can combine and parameterize with the prompts, without all the complexity and boilerplate of langchain, nor having to learn all the Python libraries and their APIs. Perfect for prototypes and experiments (like a notebook, as you suggest), and then if you find something that really works, you can hand-off a single text file to an engineer and they can make it work in a production environment.
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Langchain Is Pointless
I agree, and that's why I've been working on AIPL[0]. Our first v0.1 release should be in the next few days. https://github.com/saulpw/aipl
It's basically just a simple scripting language with array semantics and inline prompt construction, and you can drop into Python any time you like.
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Re-implementing LangChain in 100 lines of code
I also was underwhelmed by langchain, and started implementing my own "AIPL" (Array-Inspired Pipeline Language) which turns these "chains" into straightforward, linear scripts. It's very early days but already it feels like the right direction for experimenting with this stuff. (I'm looking for collaborators if anyone is interested!)
https://github.com/saulpw/aipl
langstream
- FLaNK Stack Weekly 2 October 2023
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Langchain Is Pointless
this inspired me on writing a new section in my project "Prompts on the outside" (https://github.com/rogeriochaves/litechain#prompts-on-the-ou...)
- LangChain alternative using FP approach
What are some alternatives?
modelfusion - The TypeScript library for building AI 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.
hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
gsgen - [CVPR 2024] Text-to-3D using Gaussian Splatting
multi-gpt - A Clojure interface into the GPT API with advanced tools like conversational memory, task management, and more
OuterFlightTracker - A flight tracker made in 6 hours on a flight home from OuterNet
llm - Access large language models from the command-line
shshsh - a bridge between python and shell
llm-gpt4all - Plugin for LLM adding support for the GPT4All collection of models
EdgeChains - EdgeChains.js Typescript/Javascript production-friendly Generative AI. Based on Jsonnet. Works anywhere that Webassembly does. Prompts live declaratively & "outside code in config". Kubernetes & edge friendly. Compatible with OpenAI GPT, Gemini, Llama2, Anthropic, Mistral and others