Advice on using response_model in a chat bot

[jxnl]

In a chat application, integrating the response_model=Model within a loop can be challenging. But if you change your thinking, a basic chat response class typically looks like this:

class Response(BaseModel):
    text: str

Alternatively, if we want to include a chain of thought for more complex interactions, the class expands:

class Response(BaseModel): 
    chain_of_thought: str
    text: str

This design allows parsing the chain of thought (COT) directly from the response when needed. without regex or other bs.

To accommodate more dynamic interactions, consider this mental shift in structuring the Response class:

class Response(BaseModel):
    chain_of_thought: str
    text: str
    actions: List[Action]

By adding an actions field, we can encapsulate potential actions that could be triggered in response to the chat. This structure not only retains the conversational context but also opens up possibilities for interactive and responsive chatbot behaviors.