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This repository covers the basis of prompt engineering using LangChain and OpenAI.

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Basics of Prompt Engineering and GenAI

Overview

This project aims to provide basic insights into Large Language Models (LLM), Generative AI (GenAI), and Prompt Engineering. It is divided into two courses:

  1. Course 1: Prompt Engineering

    • Objective: To help developers write effective prompts for interacting with LLMs and develop a guided chatbot.
    • Key Features:
      • Learn about different types of prompts and their impact on LLMs.
      • Understand best practices for crafting prompts.
      • Develop a guided chatbot using the OpenAI API.
  2. Course 2: Application Development using LLM and Langchain

    • Objective: To demonstrate practical applications of LLMs and Langchain in real-world scenarios.
    • Key Features:
      • Implement LLM-based solutions for various tasks.
      • Explore the capabilities of Langchain for language processing.
      • Develop applications leveraging LLMs and Langchain.

Getting Started

Prerequisites

  • Python 3.x
  • Jupyter Notebook

Installation and Usage

  1. Clone the repository: git clone <repo_url>
  2. Install the required dependencies: that can be found in the notebook itself
  3. Start Jupyter notebook: jupyter notebook
  4. Open the course notebooks in Jupyter Notebook, that can be found in respective headings

Course Structure

Course 1: Prompt Engineering

  • Module 1: Introduction to Prompt Engineering
  • Module 2: Types of Prompts
  • Module 3: Best Practices for Writing Prompts
  • Module 4: Developing a Guided Chatbot

Course 2: Application Development using LLM and Langchain

  • Module 1: Introduction to LLM and Langchain
  • Module 2: Implementing LLM-based Solutions
  • Module 3: Exploring Langchain for Language Processing
  • Module 4: Developing Applications with LLM and Langchain

License

This project is licensed under the MIT License - see the LICENSE file for

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This repository covers the basis of prompt engineering using LangChain and OpenAI.

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