gpt-json
pydantic-chatcompletion
| gpt-json | pydantic-chatcompletion | |
|---|---|---|
| 7 | 4 | |
| 726 | 52 | |
| - | - | |
| 6.8 | 4.2 | |
| about 1 month ago | 12 months ago | |
| Python | Python | |
| MIT License | - |
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gpt-json
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Structured Output from LLMs (Without Reprompting!)
I did a POC project with it recently. The guidance on gpt-3.5-turbo and gpt-4 models isn't as functional as plain gpt-3. I found I had better results using https://github.com/piercefreeman/gpt-json and it doesn't require multiple calls to the API. Not as feature filled, but it may meet your needs
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This week's top indie A.I projects, launches and resources
Gpt-json: Structured and typehinted GPT responses in Python
- GitHub - piercefreeman/gpt-json: Structured and typehinted GPT responses in Python
- Show HN: GPT-JSON – Structured and typehinted GPT responses in Python
- GPT-JSON: Structured and typehinted GPT responses in Python
pydantic-chatcompletion
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Show HN: Structed LLM outputs via Pydantic with struct-GPT
Hey everyone,
So, I stumbled upon this really cool idea of using Pydantic to deserialize and validate OpenAI's outputs over on this HN thread https://news.ycombinator.com/item?id=35821748.
It got me thinking about how I'd like a slightly tweaked API to better fit my own needs. I also found some neat stuff in jiggy-ai's Pydantic implementation for chat completion https://github.com/jiggy-ai/pydantic-chatcompletion/blob/mas..., and picked up tips from various blog posts and comments on how to up the game with the quality of a model's output by providing examples.
So, I cooked up this library - just about 200 lines of code, but it's got some nice features and it's fully tested. I hope some of you find it useful.
I'd love to hear your thoughts and feedback. Cheers!
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GPT-JSON: Structured and typehinted GPT responses in Python
Nice project! I took some inspiration from this as well as https://github.com/jiggy-ai/pydantic-chatcompletion/blob/mas... to create the following:
https://github.com/knowsuchagency/struct-gpt
I tried to make the API as intuitive as possible and added the ability to provide examples to improve the reliability and quality of the LLM's output.
- Show HN: Easy data extraction from text with Pydantic and OpenAI
What are some alternatives?
zod-chatgpt
gpt-logic - Translate the natural language generated by OpenAI's GPT models or any other large language models into JavaScript data types like booleans and objects.
jsonformer - A Bulletproof Way to Generate Structured JSON from Language Models
struct-gpt - get structured output from LLM's
emdash - 📚🧙♂️ Wisdom indexer — use AI to organize text snippets so you can actually remember & learn from what you read
evadb - Database system for AI-powered apps
open_llama - OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
llama.cpp - LLM inference in C/C++
cue - The home of the CUE language! Validate and define text-based and dynamic configuration