LangChain

Crie Aplicações de IA Generativa com LLMs (2024)

Fernando Amaral

Bem-vindo ao curso de LangChain em Python. Aprenda esta tecnologia revolucionária que permite que você desenvolva aplicações completas usando IA Generativa com Grandes Modelos de Linguagem. Este curso foi cuidadosamente desenvolvido para fornecer a você um entendimento profundo e prático das mais recentes tecnologias de processamento de linguagem natural e integração de modelos de linguagem de grande escala. O que você aprenderá:

1. Introdução: Apresentação do curso e configuração do ambiente.

2.Uso de LLMs: Exemplos práticos de uso de modelos de linguagem (LLMs) com OpenAI, incluindo completion e chat.

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What's inside

Learning objectives

Explore chains, sequential chains e router chains no langchain.
Domine o uso de langchain, incluindo caching e templates.
Utilize tools, agents e react agents para tarefas avançadas.
Crie e utilize embeddings para representar textos em espaços vetoriais.
Desenvolva aplicações web interativas com streamlit e llms.

Aprenda a armazenar e recuperar vetores usando pinecone.
Implemente buscas semânticas em documentos jurídicos com rag.
Veja exemplos práticos com o modelo gemini do google.
Aplique técnicas avançadas de nlp com langchain.
Melhore suas habilidades em ia com exemplos práticos e projetos

Explore chains, sequential chains e router chains no langchain.
Domine o uso de langchain, incluindo caching e templates.
Utilize tools, agents e react agents para tarefas avançadas.
Crie e utilize embeddings para representar textos em espaços vetoriais.
Desenvolva aplicações web interativas com streamlit e llms.
Aprenda a armazenar e recuperar vetores usando pinecone.
Implemente buscas semânticas em documentos jurídicos com rag.
Veja exemplos práticos com o modelo gemini do google.
Aplique técnicas avançadas de nlp com langchain.
Melhore suas habilidades em ia com exemplos práticos e projetos

Syllabus

Modelos da OpenAI

Apresentação

Introdução

O que é LangChain e para que Serve

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in LangChain: Crie Aplicações de IA Generativa com LLMs (2024) with these activities:

Review NLP Concepts

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Solidify your understanding of NLP concepts to enhance your learning in this course.

Browse courses on NLP

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Review materials from previous NLP courses or tutorials.
Focus on core NLP concepts such as tokenization, stemming, and part-of-speech tagging.
Practice applying these concepts using NLP libraries.

Execute LLMs

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Practice using LLMs to understand their capabilities and limitations.

Browse courses on LLMs

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Choose an LLM (e.g., OpenAI's GPT-3 or GPT-J).
Experiment with different prompts and observe the responses.
Analyze the responses to identify patterns and biases.

Explore LangChain Documentation

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Gain a thorough understanding of LangChain's capabilities and usage.

Browse courses on LangChain

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Review the official LangChain documentation.
Follow tutorials on specific topics, such as creating chains or using tools.
Experiment with the code examples provided in the tutorials.

Five other activities

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Participate in LangChain Community Discussions

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Engage with other LangChain users to exchange ideas and learn from their experiences.

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Join the LangChain community forum or Discord server.
Participate in discussions on topics related to LangChain.
Ask questions and share your knowledge with others.

Attend a LangChain Workshop

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Immerse yourself in LangChain by attending a hands-on workshop led by experts.

Browse courses on LangChain

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Find a reputable LangChain workshop in your area or online.
Register for the workshop and prepare any necessary materials.
Actively participate in the workshop, ask questions, and network with other attendees.

Explore Advanced LangChain Features

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Expand your knowledge of LangChain's capabilities by learning about advanced features.

Browse courses on LangChain

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Review documentation or tutorials on topics such as caching or agents.
Experiment with these features in your own LangChain applications.
Explore examples and best practices for using advanced features effectively.

Write a LangChain Tutorial

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Share your knowledge by creating a tutorial that guides others in using LangChain.

Browse courses on LangChain

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Choose a specific topic within LangChain to focus on.
Develop a step-by-step guide with clear explanations and code examples.
Publish your tutorial on a platform like Medium or GitHub.

Develop a LangChain Application

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Apply your knowledge by building a practical application using LangChain.

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Identify a problem or use case that LangChain can solve.
Design and implement a solution using LangChain.
Test and iterate on your application to improve its functionality.

Career center

Learners who complete LangChain: Crie Aplicações de IA Generativa com LLMs (2024) will develop knowledge and skills that may be useful to these careers: