Part 3/8:
The process involves setting up prompts with structured instructions and example responses to guide GPT-3's output, improving accuracy and relevance.
Basic Integration and Looping
The core of the implementation is a simple loop that takes user input, queries GPT-3, and displays responses. David highlights the importance of setting stop sequences (like removing "Marcus" from stopping points) to maintain smooth conversation flow. He also discusses handling multiple inputs and concatenating dialogue history to keep context.
The system saves chat logs to facilitate recall of past conversations, essential for maintaining long-term memory in the chatbot.