Saving user response and prompt into different tables based on the feedback about streamlit-feedback HOT 3 OPEN

@lpdg-pgadkari you can create a map score to differentiate between a thumbs up press and a thumbs down press.
example:

def _submit_feedback(feedback, scores, user_input, answer, cache_db):
    score = scores.get(feedback["score"])
    if score is not None:
        if score == 0:
            # insert to negative db
        elif score == 1:
            # insert to positive db

score_mappings = {"👍": 1, "👎": 0}
feedback = streamlit_feedback(feedback_type="thumbs", 
                              on_submit=_submit_feedback, 
                              key=f"feedback_{i}", 
                              optional_text_label="Please type the answer here if the given answer in not correct", 
                              kwargs={
                                  'scores': score_mappings,
                                  'user_input': user_input,
                                  'answer': answer,
                                  'cache_db': conn
                              })

from streamlit-feedback.

A couple of solutions,

• The most likely one is to revise your data model. These values probably should be in the same table
• If you want two tables, parameterise your query to either write to good_responses or bad_responses depending on the input

from streamlit-feedback.

Irrespective of whether I write to one table or two I should be able to differentiate between a thumbs up press and a thumbs down press. How do I do that?
For e.g. in the below code using streamlit, I can perform two different based on which button was pressed

st.button("👍", on_click=good_response, type='primary', key=f"thumbs_up_{i}", args=(conn, user_input, answer))
st.button("👎", on_click=bad_response, type='primary', key=f"thumbs_down_{i}", args=(conn, user_input, answer)) 

I want to save the good responses from the chatbot as it is and give a text field to let the user enter correct response in case the response form OpenAI was not good enough and save it in a table.

from streamlit-feedback.