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import os
import io
import requests
import streamlit as st
from openai import OpenAI
from PyPDF2 import PdfReader
import urllib.parse
from dotenv import load_dotenv
from openai import OpenAI
from io import BytesIO
from streamlit_extras.colored_header import colored_header
from streamlit_extras.add_vertical_space import add_vertical_space
from streamlit_extras.switch_page_button import switch_page
import json
# ---------------------- Configuration ----------------------
st.set_page_config(page_title="Building Regulations Chatbot", layout="wide", page_icon="πŸ—οΈ", initial_sidebar_state="expanded")
# Load environment variables from .env file
load_dotenv()

# Set OpenAI API key
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

# ---------------------- Session State Initialization ----------------------

if 'pdf_contents' not in st.session_state:
    st.session_state.pdf_contents = []
if 'chat_history' not in st.session_state:
    st.session_state.chat_history = []
if 'processed_pdfs' not in st.session_state:
    st.session_state.processed_pdfs = False
if 'id_counter' not in st.session_state:
    st.session_state.id_counter = 0
if 'assistant_id' not in st.session_state:
    st.session_state.assistant_id = None
if 'thread_id' not in st.session_state:
    st.session_state.thread_id = None

# ---------------------- Helper Functions ----------------------

def get_vector_stores():
    try:
        client = OpenAI()
        vector_stores = client.beta.vector_stores.list()
        return vector_stores
    except Exception as e:
        return f"Error retrieving vector stores: {str(e)}"

def fetch_pdfs(city_code):
    url = f"http://91.203.213.50:5000/oereblex/{city_code}"
    response = requests.get(url)
    if response.status_code == 200:
        data = response.json()
        print("First data:", data.get('data', [])[0] if data.get('data') else None)
        return data.get('data', [])
    else:
        st.error(f"Failed to fetch PDFs for city code {city_code}")
        return None

def download_pdf(url):
    # Add 'https://' scheme if it's missing
    if not url.startswith(('http://', 'https://')):
        url = 'https://' + url

    try:
        response = requests.get(url)
        response.raise_for_status()  # Raise an exception for bad status codes
        
        # Generate a unique filename
        filename = f"downloaded_pdf_{st.session_state.id_counter}.pdf"
        st.session_state.id_counter += 1
        
        # Save the PDF content to a file
        with open(filename, 'wb') as f:
            f.write(response.content)
        
        return filename
    except requests.RequestException as e:
        st.error(f"Failed to download PDF from {url}. Error: {str(e)}")
        return None

# Helper function to upload file to OpenAI
def upload_file_to_openai(file_path):
    try:
        file = client.files.create(
            file=open(file_path, 'rb'),
            purpose='assistants'
        )
        return file.id
    except Exception as e:
        st.error(f"Failed to upload file {file_path}. Error: {str(e)}")
        return None

def create_assistant():
    assistant = client.beta.assistants.create(
        name="Building Regulations Assistant",
        instructions="You are an expert on building regulations. Use the provided documents to answer questions accurately.",
        model="gpt-4o-mini",
        tools=[{"type": "file_search"}]
    )
    st.session_state.assistant_id = assistant.id
    return assistant.id

def chat_with_assistant(file_ids, user_message):
    for file_id in file_ids:
        print("File ID:", file_id)
    # Create a thread and attach the file to the message
    print("final file id:", file_id)
    attachments = [{"file_id": file_id, "tools": [{"type": "file_search"}]} for file_id in file_ids]
    print("attachments:", attachments)

    if st.session_state.thread_id is None:
        thread = client.beta.threads.create(
            messages=[
                {
                    "role": "user",
                    "content": user_message,
                    "attachments": attachments,
                }
            ]
        )
        st.session_state.thread_id = thread.id
    else:
        thread = client.beta.threads.messages.create(
            thread_id=st.session_state.thread_id,
            role="user",
            content=user_message,
            attachments=attachments
        )

    # The thread now has a vector store with that file in its tool resources.
    print(thread.tool_resources.file_search)
    print("assistant_id:", st.session_state.assistant_id)
    print("thread_id:", thread.id)
    run = client.beta.threads.runs.create_and_poll(
        thread_id=thread.id, assistant_id=st.session_state.assistant_id
    )
    print("run:", run)
    messages = list(client.beta.threads.messages.list(thread_id=thread.id, run_id=run.id))

    message_content = messages[0].content[0].text
    annotations = message_content.annotations
    citations = []
    for index, annotation in enumerate(annotations):
        message_content.value = message_content.value.replace(annotation.text, f"[{index}]")
        if file_citation := getattr(annotation, "file_citation", None):
            cited_file = client.files.retrieve(file_citation.file_id)
            citations.append(f"[{index}] {cited_file.filename}")

    print(message_content.value)
    print("\n".join(citations))
    return message_content.value, citations



# ---------------------- Streamlit App ----------------------

page = st.sidebar.selectbox("Choose a page", ["Home", "Documents", "Admin"])

if page == "Home":
    st.title("πŸ—οΈ Building Regulations Chatbot", anchor=False)

    # Sidebar improvements
    with st.sidebar:
        colored_header("πŸ“„ Selected Documents", description="Documents for chat")
        if 'selected_pdfs' in st.session_state and st.session_state.selected_pdfs:
            for pdf in st.session_state.selected_pdfs:
                st.write(f"- {pdf['doc_title']}")
        else:
            st.write("No documents selected. Please go to the Documents page.")

    # Main chat area improvements
    colored_header("πŸ’¬ Chat", description="Ask questions about building regulations")

    # Display chat messages with improved styling
    for chat in st.session_state.chat_history:
        with st.container():
            if chat['role'] == 'user':
                st.markdown(f"""
                <div class="chat-message user">
                    <div><strong>You</strong></div>
                    <div class="message-content">{chat['content']}</div>
                </div>
                """, unsafe_allow_html=True)
            else:
                st.markdown(f"""
                <div class="chat-message assistant">
                    <div><strong>Assistant</strong></div>
                    <div class="message-content">{chat['content']}</div>
                </div>
                """, unsafe_allow_html=True)

    # Chat input improvements
    with st.form("chat_form", clear_on_submit=True):
        user_input = st.text_area("Ask a question about building regulations...", height=100)
        col1, col2 = st.columns([3, 1])
        with col2:
            submit = st.form_submit_button("Send", use_container_width=True)

    if submit and user_input.strip() != "":
        # Add user message to chat history
        st.session_state.chat_history.append({"role": "user", "content": user_input})
        
        if not st.session_state.file_ids:
            st.error("Please process PDFs first.")
        else:
            with st.spinner("Generating response..."):
                try:
                    response, citations = chat_with_assistant(st.session_state.file_ids, user_input)
                    # Add assistant response to chat history
                    st.session_state.chat_history.append({"role": "assistant", "content": response+"\n\n"+"\n".join(citations)})
                except Exception as e:
                    st.error(f"Error generating response: {str(e)}")

        # Rerun the app to update the chat display
        st.rerun()

    # Footer improvements
    add_vertical_space(2)
    st.markdown("---")
    col1, col2 = st.columns(2)
    with col1:
        st.caption("Powered by OpenAI GPT-4 and Pinecone")
    with col2:
        st.caption("Β© 2023 Your Company Name")

elif page == "Documents":
    st.title("πŸ“š Document Selection")

    city_code_input = st.text_input("Enter city code:", key="city_code_input")
    load_documents_button = st.button("Load Documents", key="load_documents_button")

    if load_documents_button and city_code_input:
        with st.spinner("Fetching PDFs..."):
            pdfs = fetch_pdfs(city_code_input)
            if pdfs:
                st.session_state.available_pdfs = pdfs
                st.success(f"Found {len(pdfs)} PDFs")
            else:
                st.error("No PDFs found")

    if 'available_pdfs' in st.session_state:
        st.write(f"Total PDFs: {len(st.session_state.available_pdfs)}")
        selected_pdfs = []
        for pdf in st.session_state.available_pdfs:
            title = f"{pdf.get('doc_title', 'Untitled')} - {pdf.get('doc_type', 'No type')}"
            if pdf.get('number'):
                title += f" ({pdf['number']})"
            if st.checkbox(title, key=f"pdf_{pdf['file_href']}"):
                selected_pdfs.append(pdf)

        if st.button("Process Selected PDFs"):
            if selected_pdfs:
                st.session_state.selected_pdfs = selected_pdfs
                st.session_state.assistant_id = create_assistant()
                with st.spinner("Processing PDFs and creating/updating assistant..."):
                    file_ids = []
                    for pdf in selected_pdfs:
                        file_name = download_pdf(pdf['file_href'])
                        if file_name:
                            file_path = f"./{file_name}"
                            file_id = upload_file_to_openai(file_path)
                            if file_id:
                                file_ids.append(file_id)
                            else:
                                st.warning(f"Failed to upload {pdf['doc_title']}. Skipping this file.")
                        else:
                            st.warning(f"Failed to download {pdf['doc_title']}. Skipping this file.")
                    st.session_state.file_ids = file_ids
                st.success("PDFs processed successfully. You can now chat on the Home page.")
            else:
                st.warning("Select at least one PDF.")

    if st.button("Go to Home"):
        switch_page("Home")

elif page == "Admin":
    st.title("πŸ”§ Admin Panel")
    colored_header("Vector Stores Information", description="List of all vector stores")
    
    vector_stores = get_vector_stores()
    json_vector_stores = json.dumps([vs.model_dump() for vs in vector_stores])
    st.write(json_vector_stores)

    # Add a button to go back to the main page
    if st.button("Back to Home"):
        switch_page("Home")