"""
🇬🇧 Module: comparer.py()
Purpose: Compares two portfolios using LLM. Fetches metrics for both and builds a unified comparison prompt.

🇷🇺 Модуль: comparer.py
Назначение: сравнение двух инвестиционных портфелей с помощью LLM. Получает метрики обоих портфелей, формирует промпт и возвращает потоковый результат.
"""

import asyncio
from typing import Generator
from services.output_api import extract_portfolio_id, fetch_metrics_async
from services.llm_client import llm_service
from prompts.system_prompts import COMPARISON_SYSTEM_PROMPT
from prompts.reference_templates import REFERENCE_COMPARISON_PROMPT


class PortfolioComparer:
    """Main use-case class for comparing two portfolios."""

    def __init__(self, llm=llm_service, model_name: str = "meta-llama/Meta-Llama-3.1-8B-Instruct"):
        self.llm = llm
        self.model_name = model_name

    def run(self, text1: str, text2: str) -> Generator[str, None, None]:
        """Stream comparison results between two portfolios."""
        id1 = extract_portfolio_id(text1)
        id2 = extract_portfolio_id(text2)

        if text1 == text2:
            yield "❗ Please, give me a two difference portfolio ID."
            return
        if not id1 or not id2:
            yield "❗ One of two portfolios is empty or incorrect."
            return

        yield "⏳ Working..."
        try:
            m1 = asyncio.run(fetch_metrics_async(id1))
            m2 = asyncio.run(fetch_metrics_async(id2))
        except Exception as e:
            yield f"❌ There are issue via collecting data: {e}"
            return

        if not m1 or not m2:
            yield "❗ One of two portfolios is empty or has incorrect data."
            return

        m1_text = ", ".join(f"{k}: {v}" for k, v in m1.items())
        m2_text = ", ".join(f"{k}: {v}" for k, v in m2.items())

        prompt = (
            f"{REFERENCE_COMPARISON_PROMPT}\n"
            f"Используй эти данные для сравнения:\n"
            f"Портфель A: {m1_text}\n"
            f"Портфель B: {m2_text}"
        )

        try:
            messages = [
                {"role": "system", "content": COMPARISON_SYSTEM_PROMPT},
                {"role": "user", "content": prompt},
            ]

            partial = ""
            for delta in self.llm.stream_chat(messages=messages, model=self.model_name):
                partial += delta
                yield partial

        except Exception as e:
            yield f"❌ Ошибка при сравнении портфелей через LLM: {e}"