import gradio as gr
import os
from openai import OpenAI
from stock_utils import get_multi_stock_data

# Initialize OpenAI client using Hugging Face secret
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

def analyze_stocks(ticker_input):
    try:
        # Split input into a list of tickers
        tickers = [t.strip().upper() for t in ticker_input.split(',') if t.strip()]
        if not tickers:
            return "Please enter at least one valid stock ticker."

        # Get stock data for all tickers
        stock_data_list = get_multi_stock_data(tickers)

        # Format prompt for the agent
        formatted_data = "\n\n".join([str(data) for data in stock_data_list])
        prompt = (
            "You are a financial analyst. Analyze the following stock data for multiple companies and for each, provide:\n"
            "1. A BUY / HOLD / SELL recommendation\n"
            "2. Reason for the recommendation\n"
            "3. Summary in bullet points\n\n"
            f"Stock Data:\n{formatted_data}"
        )

        # Call GPT-4o to analyze all stocks
        response = client.chat.completions.create(
            model="gpt-4o",
            messages=[{"role": "user", "content": prompt}]
        )

        raw_text = response.choices[0].message.content.strip()

        if raw_text.startswith("```") and raw_text.endswith("```"):
            raw_text = raw_text[3:-3].strip()
        elif raw_text.startswith("'''") and raw_text.endswith("'''"):
            raw_text = raw_text[3:-3].strip()
        elif raw_text.startswith('"') and raw_text.endswith('"'):
            raw_text = raw_text[1:-1].strip()

        return raw_text

    except Exception as e:
        return f"❌ Unexpected error: {str(e)}"

# Gradio app UI
demo = gr.Interface(
    fn=analyze_stocks,
    inputs=gr.Textbox(label="Enter Stock Tickers (comma-separated, e.g., AAPL, MSFT, TSLA)"),
    outputs=gr.Textbox(label="Agent Recommendations"),
    title="📊 Multi-Stock AI Advisor Agent",
    description="Enter multiple stock tickers to get GPT-4o-powered insights and recommendations over multiple timeframes."
)

demo.launch()