§Intent Classification: Inconsistent Responses

[TahaTobaili]

User Experience:

As the user is watching the video, they can chat with AiDA about it. Their questions, might require an in depth response aided by a nice chart or it might be a simple response. Hence, a chart is not always necessary in this case.

What needs to be done:

To mitigate this redundancy, a nice way is to classify the user's intent, as a start if they are looking for a summary then yes generate a chart and audio file (text-to-speech) as well.

For that check function classify_intent(user_input) it attempts to classify whether the user is requesting a summary or something else via a ChatGPT call. The responses are inconsistent and not always accurate.

To address this, the following steps need to be implemented:

1. Prompt: We need to make sure ChatGPT response is precisely "True" or "False" to treat the output as a boolean with ast.literal_eval(response.content). It might be that GPT is responding with something like "true" or "true.." or "yes, it is a summary" or the like. Keep playing with the prompt to reach consistent output.

2. Function Calling: Use a json schema and function calling to return the response to a specific json key, read this.

   Bonus Points: Figure out Function Calling in LangChain!

3. Testing Robustness: Need to be tested sufficiently to confirm that the intent is correctly classified as "True" if request relates to a summary or "False" for anything else.