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# Chatbot Application

## Overview

This chatbot application utilizes a language model to facilitate interactive conversations. It's important to note that large language models (LLMs) like the one used in this chatbot do not possess any inherent concept of state or memory. Consequently, any chat history must be managed externally and passed into the model with each new message.

In this implementation, we employ a list of custom objects to track chat history. Due to the constraints on the amount of content that the model can process at once, we implement a pruning mechanism. This ensures that older messages are deleted as needed, maintaining enough capacity to accommodate the user’s current input and the model's responses.

### Important Note on Responses

The responses generated by the chatbot are solely based on the capabilities of the underlying foundation model, which means they do not rely on any external data sources. As such, the chatbot may occasionally produce inaccurate or fabricated information, a phenomenon known as "hallucination." 

## Use Cases

The chatbot pattern is particularly well-suited for the following scenarios:

- **Interactive User Conversations**: Engaging users in simple, interactive dialogues without requiring specialized knowledge or data.

This design allows for dynamic interactions while managing the limitations inherent in language models effectively.

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