import os
import gradio as gr
from extract_pdf import extract_text_from_pdf, extract_text_from_scanned_pdf
from vector_store import add_document, search
from stock_data import get_stock_data
from sentiment import analyze_sentiment

# Create folders if not exist
DATA_FOLDER = "data"
FAISS_FOLDER = "faiss_index"
os.makedirs(DATA_FOLDER, exist_ok=True)
os.makedirs(FAISS_FOLDER, exist_ok=True)

# 1️⃣ Process uploaded PDF and add to FAISS
def process_pdf(file):
    """Process uploaded PDF and add to FAISS"""
    file_path = os.path.join(DATA_FOLDER, file.name)
    with open(file_path, "wb") as f:
        f.write(file.read())

    # Extract text using available methods
    text = extract_text_from_pdf(file_path) or extract_text_from_scanned_pdf(file_path)
    add_document(text, file.name)
    return f"✅ PDF '{file.name}' indexed successfully!"


# 2️⃣ Search FAISS for relevant PDFs
def query_pdf(query):
    """Search FAISS index for relevant documents."""
    results = search(query)

    response = "📌 **Top Matching Documents:**\n\n"
    for res in results:
        response += f"📄 **{res.metadata['id']}**\n{text[:500]}...\n\n"

    # Sentiment analysis
    response += "\n📊 **Sentiment Analysis:**\n"
    for res in results:
        sentiment = analyze_sentiment(res.page_content)
        response += f"📄 **{res.metadata['id']}** → Sentiment: {sentiment}\n"

    return response


# 3️⃣ Fetch Live Stock Market Data
def get_stock_info(ticker):
    """Fetch real-time stock price from Yahoo Finance."""
    stock_data = get_stock_data(ticker)
    return f"\n📈 Stock Price for {ticker}: ${stock_data['price']}"


# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# Stock Analysis PDF Indexer")

    # File Upload for PDFs
    pdf_upload = gr.File(label="Upload PDFs", file_count="multiple")
    upload_button = gr.Button("Upload and Index PDF")
    upload_message = gr.Textbox(label="Upload Status", interactive=False)

    # PDF Query Input
    query_input = gr.Textbox(label="Query PDFs")
    query_output = gr.Textbox(label="Query Results", interactive=False)

    # Stock Ticker Input
    stock_input = gr.Textbox(label="Enter Stock Ticker (e.g., AAPL)")
    stock_output = gr.Textbox(label="Stock Data", interactive=False)

    # Actions
    upload_button.click(process_pdf, inputs=pdf_upload, outputs=upload_message)
    query_input.submit(query_pdf, inputs=query_input, outputs=query_output)
    stock_input.submit(get_stock_info, inputs=stock_input, outputs=stock_output)

# Launch the Gradio interface
demo.launch()