import streamlit as st
from st_pages import Page, show_pages
from openai import OpenAI
import urllib.parse
from whisper_stt import whisper_stt

# Set page configuration
st.set_page_config(layout="wide")
show_pages([Page("app.py", "Home", "🏠")])

# Initialize session state variables
if 'paused' not in st.session_state:
    st.session_state.paused = False
if 'question_text' not in st.session_state:
    st.session_state.question_text = ""
if 'submitted' not in st.session_state:
    st.session_state.submitted = False   
if 'response_content' not in st.session_state:
    st.session_state.response_content = []
if 'stopped' not in st.session_state:
    st.session_state.stopped = False
if 'function_call_count' not in st.session_state:
    st.session_state.function_call_count = 0       
if 'transcribed_text' not in st.session_state:
    st.session_state.transcribed_text = ""
if 'last_processed_text' not in st.session_state:
    st.session_state.last_processed_text = ""
if 'questions' not in st.session_state:
    st.session_state.questions = []

def on_stop():
    st.session_state.stopped = True

def handle_enter(key):
    if key == "ctrl+enter":
        new_question = st.session_state.question_input
        print(f"handle_enter called. new_question: '{new_question}'")
        print(f"session state: {st.session_state}")

with st.sidebar:
    api_key = st.text_input("API Key", key="chatbot_api_key", type="password")

    col1, col2 = st.columns(2)

    with col1:
        # Call whisper_stt without a callback
        transcribed_text = whisper_stt(
            openai_api_key=api_key,
            language='en'
        )
        if transcribed_text:
            st.session_state.question_text = transcribed_text

        # Check if new transcription is available
        if transcribed_text and transcribed_text != st.session_state.transcribed_text:
            st.session_state.transcribed_text = transcribed_text
            st.session_state.question_text = transcribed_text
            st.session_state.submitted = True

    if st.session_state.question_text:
        st.write("Current Question:", st.session_state.question_text)

    if 'question_input' in st.session_state and st.session_state.question_input:
        st.write("Current Question Input:", st.session_state.question_input)
        
    with col2:
        st.button(label='Stop', on_click=on_stop)
   
    # Create an input for the question and use new_question directly
    new_question = st.text_area("Question", 
        value=st.session_state.question_text or "", 
        height=150, 
        key="question_input",
        on_change=handle_enter,
        args=("ctrl+enter",)
    )
    print(f"After text_area, new_question: '{new_question}'")
    # Check if new_question has changed and is not empty
    if new_question and new_question != st.session_state.question_text:
        st.session_state.question_text = new_question
        st.session_state.submitted = True

    st.markdown("## Navigation")
    for i, q in enumerate(st.session_state.questions):
        st.write(f"Q{i+1}: {q['question']}")

if st.session_state.question_text and not api_key:
    st.info("Please add your OpenAI API key to continue.")
    st.stop()

if st.session_state.submitted and not st.session_state.stopped:
    st.session_state.questions.append({'question': st.session_state.question_text, 'response': ''})
    
    client = OpenAI(api_key=api_key)
    st.session_state.messages = [{"role": "user", "content": st.session_state.question_text}]

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=st.session_state.messages,
        stream=True
    )

    # Create a placeholder for the streamed response
    response_placeholder = st.empty()
    response_text = ""

    for chunk in response:
        if st.session_state.stopped:
            st.session_state.stopped = False
            st.session_state.submitted = False
            break
        else:
            if chunk and chunk.choices[0].delta.content:
                response_text += chunk.choices[0].delta.content
                # Update the placeholder with the current response text
                response_placeholder.markdown(f"**Answer:** {response_text}")

    if response_text:
        st.session_state.questions[-1]['response'] = response_text

    st.session_state.submitted = False
    st.session_state.stopped = False

# Display previous questions and answers
for i, q in enumerate(st.session_state.questions[:-1]):  # Exclude the last question
    st.markdown(f"### Question {i+1}: {q['question']}")
    st.markdown(f"**Answer:** {q['response']}")

# Display the latest question separately
if st.session_state.questions:
    latest_q = st.session_state.questions[-1]
    st.markdown(f"### Question {len(st.session_state.questions)}: {latest_q['question']}")
    # The answer for the latest question is already being streamed in the placeholder