aipl
modelfusion
aipl | modelfusion | |
---|---|---|
4 | 18 | |
119 | 952 | |
- | 12.3% | |
9.2 | 9.9 | |
6 months ago | 2 days ago | |
Python | TypeScript | |
MIT 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.
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
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?
hamilton - Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage and metadata. Runs and scales everywhere python does.
langchainjs - 🦜🔗 Build context-aware reasoning applications 🦜🔗
multi-gpt - A Clojure interface into the GPT API with advanced tools like conversational memory, task management, and more
langroid - Harness LLMs with Multi-Agent Programming
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.
llm - Access large language models from the command-line
async-interval-job - ✨ setInterval for promises and async/sync functions. Support graceful shutdown and prevent multiple executions from overlapping in time.
llm-gpt4all - Plugin for LLM adding support for the GPT4All collection of models
chatflow - Leveraging LLM to build Conversational UIs
llm-api - Fully typed & consistent chat APIs for OpenAI, Anthropic, Groq, and Azure's chat models for browser, edge, and node environments.
meta-parser - Universal meta-tag scrapper for Node.js. Works both with CJS and ESM modules.