parsel
transynthetical-engine
parsel | transynthetical-engine | |
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7 | 6 | |
377 | 26 | |
- | - | |
0.0 | 6.2 | |
8 months ago | about 1 year ago | |
Python | TypeScript | |
- | MIT License |
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parsel
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ChatGPT-Linux-Assistant
Parsel : A (De-)compositional Framework for Algorithmic Reasoning with Language Models
https://arxiv.org/abs/2212.10561
Here's a notebook with an introduction:
https://github.com/ezelikman/parsel/blob/main/parsel.ipynb
And here's a GUI interface the author has been developing:
http://zelikman.me/parsel/interface.html
I've been working on an augmented large language model that given these few-shot exemplars can build the below fully-functional ToDo App: ==
https://github.com/williamcotton/transynthetical-engine/tree...
https://www.williamcotton.com/articles/junie-browser-builder...
All of this is still very rough around the edges, prone to errors of various kinds, and generally not ready for prime time, but anyone is welcome to play around with what is there!
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We're never getting rid of ChatGPT
I agree. My goal, which seems very achievable from my current research, is to write formal specifications in English and generate functioning code.
One of my favorite recent projects is called Parsel:
Parsel : A (De-)compositional Framework for Algorithmic Reasoning with Language Models
https://arxiv.org/abs/2212.10561
Here's a notebook with an introduction:
https://github.com/ezelikman/parsel/blob/main/parsel.ipynb
And here's a GUI interface the author has been developing:
http://zelikman.me/parsel/interface.html
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[R] Parsel: A (De-)compositional Framework for Algorithmic Reasoning with Language Models - Stanford University Eric Zelikman et al - Beats prior code generation sota by over 75%!
Another is, "why design a new language instead of writing this as, e.g., a Python library?" My response is we did. Internally, Parsel is in Python, and a "Function" class already exists - you can find it on GitHub. Still, you need a process to generate implementations and select one satisfying the constraints, which we call the compiler.
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Parsel: A (De-)compositional Framework for Algorithmic Reasoning with Language Models - Stanford University Eric Zelikman et al - Beats prior code generation sota by over 75%!
We made this available here!: https://github.com/ezelikman/parsel
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Researchers at Stanford Introduce Parsel: An Artificial Intelligence AI Framework That Enables Automatic Implementation And Validation of Complex Algorithms With Code Large Language Models LLMs
👉 For code language models, every token is a new chance to break a program. What if LLMs wrote code like people, decomposing programs into solvable parts? They can solve competition-level coding problems by writing natural language programs in Parsel, beating prior SoTA by >75%! Quick Read: https://www.marktechpost.com/2023/01/29/researchers-at-stanford-introduce-parsel-an-artificial-intelligence-ai-framework-that-enables-automatic-implementation-and-validation-of-complex-algorithms-with-code-large-language-models-llms/ Paper: http://zelikman.me/parselpaper/parsel\_paper.pdf Github: https://github.com/ezelikman/parsel 🚀 Stay up-to-date on the latest AI news in just 3 minutes with our daily digest. Join a community of thousands of AI professionals and stay informed: https://marktechpost-newsletter.beehiiv.com/
transynthetical-engine
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Native JSON Output from GPT-4
Here’s an approach to return just JavaScript:
https://github.com/williamcotton/transynthetical-engine
The key is the addition of few-shot exemplars.
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The Dual LLM pattern for building AI assistants that can resist prompt injection
I think the two-layer approach is worthwhile if only for limiting tokens!
Here’s an example of what I mean:
https://github.com/williamcotton/transynthetical-engine#brow...
By keeping the main discourse between the user and the LLM from containing all of the generated code and instead just using that main “thread” to orchestrate instructions to write code it allows for more back-and-forth.
It’s a good technique in general!
I’m still too paranoid to execute instructions via email without a very limited set of abilities!
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Prompt Engineering vs. Blind Prompting
Here is an example of some prompt engineering in order to build augmentations for factual question-and-answer as well as building web applications:
https://github.com/williamcotton/transynthetical-engine
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Ask HN: People who were laid off or quit recently, how are you doing?
Hey Simon! I've been digging your writings on LLMs lately.
I've been having some decent luck with some of the approaches that I've discussed in the following articles and projects:
From Prompt Alchemy to Prompt Engineering: An Introduction to Analytic Augmentation: https://github.com/williamcotton/empirical-philosophy/blob/m...
https://www.williamcotton.com/articles/writing-web-applicati...
https://github.com/williamcotton/transynthetical-engine
I'd love to hear your thoughts on the matter!
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We need to tell people ChatGPT will lie to them, not debate linguistics
Sure you can. The easiest way is to go to https://chat.openai.com/chat and paste in a Wikipedia article.
There are more involved manners like this: https://github.com/williamcotton/transynthetical-engine/blob...
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ChatGPT-Linux-Assistant
Parsel : A (De-)compositional Framework for Algorithmic Reasoning with Language Models
https://arxiv.org/abs/2212.10561
Here's a notebook with an introduction:
https://github.com/ezelikman/parsel/blob/main/parsel.ipynb
And here's a GUI interface the author has been developing:
http://zelikman.me/parsel/interface.html
I've been working on an augmented large language model that given these few-shot exemplars can build the below fully-functional ToDo App: ==
https://github.com/williamcotton/transynthetical-engine/tree...
https://www.williamcotton.com/articles/junie-browser-builder...
All of this is still very rough around the edges, prone to errors of various kinds, and generally not ready for prime time, but anyone is welcome to play around with what is there!
What are some alternatives?
chatgpt-arcana.el - Put ChatGPT in your emacs and give yourself arcane powers 🔮
simpleaichat - Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
chatgpt-linux-assistant - An ai assistant in your CLI. But it knows what's on your system and can help you get things done.
NeMo-Guardrails - NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
geppetto - Your personal assistant with ChatGPT and Linux superpowers, ready for any task!
chrono - A natural language date parser in Javascript
yolo-ai-cmdbot - AI bot that translates your question to a command and executes it yolo style
clevercli - ChatGPT powered CLI utilities. Easily add new prompt types in ~/.clevercli/
openai-cookbook - Examples and guides for using the OpenAI API
empirical-philosophy - A collection of empirical experiments using large language models and other neural network architectures to test the usefulness of metaphysical constructs.