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Welcome to this comprehensive guide on building an interactive chatbot powered by OpenAI’s GPT-3.5 and GPT-4 models. In this tutorial, you’ll learn how to:
  • Craft effective prompts for both word-based and conversational APIs
  • Manage conversation history to maintain context
  • Assemble building blocks for a responsive customer-service chatbot
  • Deploy a sample chatbot for a fictional fast-food burger restaurant
By the end of this lesson, you’ll have a solid understanding of how to integrate OpenAI’s chat completions into your applications and deliver a seamless conversational experience.
Make sure you have an active OpenAI API key. You can sign up at OpenAI.

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Word Completion vs. Chat Completion

FeatureWord CompletionChat Completion
API Endpoint/v1/completions/v1/chat/completions
Input FormatPlain prompt stringArray of structured messages
Best Use CasesShort text generation, code fixesStateful conversations, multi-turn dialogues
Model Examplestext-davinci-003gpt-3.5-turbo, gpt-4
Context ManagementLimited (token-based)Full message history, system/user/assistant roles

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What You’ll Build

  1. Prompt Engineering: Learn how to frame user requests for accurate responses.
  2. Context Storage: Implement a history buffer to pass previous messages to the API.
  3. Chat Loop: Create an interactive loop to send and receive messages.
  4. Fast-Food Bot: Deploy a customer-service chatbot that takes orders, answers FAQs, and handles errors.
Let’s dive into the details!

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