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Api Alternatives
Similar projects and alternatives to api
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guidance
Discontinued A guidance language for controlling large language models. [Moved to: https://github.com/guidance-ai/guidance] (by microsoft)
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SurveyJS
Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
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hof
Framework that joins data models, schemas, code generation, and a task engine. Language and technology agnostic.
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program
Discontinued An open-source codebase for sharing programming solutions. Good collection of `good first issue`
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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one-day-one-language
Cómo dar en un día tus primeros pasos en cada lenguaje de programación. Introducción, configuración e instalación, usos habituales, fundamentos, sintaxis y próximos pasos.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better api alternative or higher similarity.
api reviews and mentions
Posts with mentions or reviews of api.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-16.
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Guidance: A guidance language for controlling large language models
Logit-bias guidance goes a long way -- LLM structure for regex, context-free grammars, categorization, and typed construction. I'm working on a hosted and model-agnostic version of this with thiggle
[0] https://thiggle.com
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The Most Underrated Application of LLMs
We use a similar trick and expose it via an API. Much easier to parse when you can guarantee the shape of the output
[0] https://thiggle.com/
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What we learned from using GPT for 500k+ classifications
I just released a zero-shot classification API built on LLMs https://github.com/thiggle/api. It always returns structured JSON and only the relevant categories/classes out of the ones you provide.
LLMs are excellent reasoning engines. But nudging them to the desired output is challenging. They might return categories outside the ones that you determined. They might return multiple categories when you only want one (or the opposite — a single category when you want multiple). Even if you steer the AI toward the correct answer, parsing the output can be difficult. Asking the LLM to output structure data works 80% of the time. But the 20% of the time that your code parses the response fails takes up 99% of your time and is unacceptable for most real-world use cases.
[0] https://twitter.com/mattrickard/status/1678603390337822722
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A note from our sponsor - SaaSHub
www.saashub.com | 4 May 2024
Stats
Basic api repo stats
3
151
6.5
8 months ago
thiggle/api is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of api is MDX.
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