doesn't take context into consideration. gets confused easily.

[alan-ai-learner]

Pls, help to remove this unwanted behavior, or suggest some ways to do it. Thanks

[chiranshu14]

Pls, help to remove this unwanted behavior, or suggest some ways to do it. Thanks

@alan-ai-learner You can try fine tuning it with custom dataset to improve the quality of responses. But don't expect it to be perfect. Can you tell your use case? So that I can suggest better option if I know?

[alan-ai-learner]

I just want to make a chatbot, that is like, two friends were talking to each other, it not some domain based but a simple and usual conversation that will held between two friends, so that my aim.

[chiranshu14]

If you have to use GPT, then best thing would be to fine-tune with super clean dataset.

If you always want clean responses, try rasa, it will for sure give you clean results. But you will have to build your own training dataset and response sets. It won't be as creative as GPT. But you can maybe integrate GPT inside rasa (I'm doing this). For some basic intents, use your predefined responses, and for fallback_intents get GPT response. It will get heavier though.

[alan-ai-learner]

@chiranshu14 thanks a lot for your response, btw my chatbot wasn't domain specific, I don't know any predefined intent as of now, I just need a chatbot that can do a casual conversation with the user and remember the context for a reasonable time.