Structured Outputs OpenAI: JSON Conforme allo Schema Senza Validation Hell

«Structured Outputs OpenAI: JSON Conforme allo Schema Senza Validation Hell» è un corso online di ChatGPT e OpenAI di livello principiante, tenuto da InsightLearn Curated AI su InsightLearn. Il percorso comprende 7 lezioni organizzate in 2 sezioni, per una durata complessiva di 5h 0m. Strict JSON Schema mode di OpenAI: il modello è vincolato allo schema. Niente più parsing fallito, retry, validation custom.

Descrizione del corso

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Strict JSON Schema mode di OpenAI: il modello è vincolato allo schema. Niente più parsing fallito, retry, validation custom.

Cosa imparerai

  • Curated from public resources. Strict JSON Schema mode di OpenAI: il modello è vincolato allo schema. Niente più parsing fallito, retry, validation custom.

Programma del corso

  1. JSON mode vs Structured Outputs strict (10 min)
  2. Primo schema strict in Python (10 min)
  3. Pydantic + OpenAI SDK (10 min)
  4. Union, enum, nested object (10 min)
  5. Refusal handling (10 min)
  6. Schema design tip per LLM (10 min)
  7. Performance e latency impact (10 min)

Dalle lezioni

Estratto della trascrizione di «JSON mode vs Structured Outputs strict»

Today I want to talk about a new feature that's just come to Elama which is structured outputs now This is where you're able to restrict The output that comes back from Elama to a specific Format defined by a JSON schema and that means that you're able to get structured output from it And this is something that's existed for a while in Say providers like open AI also existed in together as well But now we can do it with open models on our own machine. Let me show you how so this is an example of Elama how we would do things previously. This is just using JSON format from Elama. If we run that, it's just…

Estratto della trascrizione di «Primo schema strict in Python»

Hey there, how's it going everybody? In this video we're going to be learning how to use pidantic schemas to validate our API request and responses in FastAPI. So in this series so far we've set up the basic structure of our API with some get endpoints that return our post. But right now we're just returning plain dictionaries with no validation and we don't have any way to create posts through the API yet. So in this video we're going to introduce pidantic and create schema file. with requests and response models. We'll add field validations for things like minimum and maximum length. Then we'll update our get endpoints to use those response models and create a post endpoint…

Estratto della trascrizione di «Pydantic + OpenAI SDK»

With Podantic AI, building agents has become faster and more efficient than ever before. In this video, I'm going to show you how it works, discuss the main benefits, and unpack the core elements of the framework by building a real-world example of a customer support agent. Let's get started. Podantic AI is developed by the team behind Podantic, the number one data validation library for Python. The mission behind Podantic AI is to do for generative AI what fast API did for web development. That means creating a framework that's intuitive, excellent, generates the development process and reduces bugs with type checking and data validation. When we talk about agents, we usually mean function calling with LLMs, that is,…

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Domande frequenti

Quanto dura il corso Structured Outputs OpenAI: JSON Conforme allo Schema Senza Validation Hell?

Il corso dura 5h 0m in totale, con 7 lezioni suddivise in 2 sezioni, da seguire online al proprio ritmo.

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Il corso è di livello principiante e non indica requisiti specifici di ingresso.

Il corso rilascia un certificato?

Sì: al completamento del corso ricevi un certificato di completamento verificabile online.