import streamlit as st
import pandas as pd
from data_manager_bziiit import get_prompts
from session import get_rag

prompts = [] 
def get_prompts_list():
    st.header("Prompts")
    prompts = get_prompts()

    # Check if prompts is a list of dictionaries
    if isinstance(prompts, list) and all(isinstance(i, dict) for i in prompts):
        # Create a DataFrame
        df = pd.DataFrame(prompts)

        # Check if 'name', 'context', and 'text' are in df columns
        if 'name' in df.columns and 'context' in df.columns and 'text' in df.columns:
            # Extract 'name' from 'context' dictionary
            df['context'] = df['context'].apply(lambda x: x.get('name') if isinstance(x, dict) else x)

            # Get first 50 characters from 'text' and add "..." at the end
            df['text'] = df['text'].apply(lambda x: x[:50] + "..." if isinstance(x, str) else x)

            # Group by 'context'
            grouped = df.groupby('context')

            for name, group in grouped:
                st.subheader(name)  # Display the context name as a subheader
                for i, row in group.iterrows():
                    col1, col2, col3, col4 = st.columns((1, 2, 2, 1))
                    col1.write(i)  # index
                    col2.write(row['name'])  # name
                    col3.write(row['text'])  # text
                    button_phold = col4.empty()  # create a placeholder
                    do_action = button_phold.button('Show More', key=i)
                    if do_action:
                        st.text(prompts[i]['text'])  # Display the full text
                        button_phold.empty()  # remove button
        else:
            st.write("Data does not contain 'name', 'context', and 'text' fields.")
    else:
        st.write("Data is not in the expected format (list of dictionaries).")


def prompt_execution():
    prompts = get_prompts()

    selected_prompt = st.selectbox("Choisissez un prompt", prompts, format_func=lambda prompt: prompt['name'])
    if selected_prompt:
        return selected_prompt
    
    return None


def execute_prompt(prompt):
    vectorstore, chain = get_rag()

    st.header(prompt['name'])
    st.text(prompt['text'])

    if vectorstore and chain:
        st.success("Vectorestore et chain trouvés")
        
        if st.button("Exécuter le prompt"):
            with st.spinner("Processing..."):
                ambition = chain.invoke(prompt['text'])
                st.markdown("### Réponse :")
                st.markdown(ambition.content)