March 2025
Intermediate to advanced
422 pages
10h 54m
Portuguese (Portugal, Brazil)
Content preview from Engenharia prompt para IA generativa
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Capítulo 4. Técnicas avançadas para geração de texto com LangChain
Este trabalho foi traduzido com recurso a IA. Agradecemos o teu feedback e comentários: translation-feedback@oreilly.com
A utilização de técnicas simples de engenharia de prompt funcionará frequentemente para a maioria das tarefas, mas ocasionalmente terás de utilizar um conjunto de ferramentas mais poderoso para resolver problemas complexos de IA generativa. Esses problemas e tarefas incluem:
- Comprimento do contexto
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Resume um livro inteiro numa sinopse digerível.
- Combinação de entradas/saídas LLM sequenciais
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Criar uma história para um livro, incluindo as personagens, o enredo e a construção do mundo.
- Executa tarefas de raciocínio complexas
-
LLMs actuando como agentes. Por exemplo, podes criar um agente LLM para te ajudar a atingir os teus objetivos pessoais de fitness.
Para enfrentar habilmente estes desafios complexos de IA generativa, é altamente benéfico familiarizares-te com a LangChain, uma estrutura de código aberto. Esta ferramenta simplifica e melhora substancialmente os fluxos de trabalho do teu LLM.
Introdução à LangChain
LangChain é uma estrutura versátil que permite a criação de aplicações utilizando LLMs e está disponível como um pacote Python e TypeScript. O seu princípio central é que as aplicações mais impactantes e distintas não farão apenas a interface com um modelo de linguagem através de uma API, mas também:
- Aumenta a sensibilização para os dados
-
O quadro tem por objetivo estabelecer ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.