from app.database.models import Summary
from app.database.repositories import MemoryRepository
from app.llm.prompts import SUMMARY_PROMPT
from app.memory.context_builder import ContextBuilder


class Summarizer:
    def __init__(self, memory: MemoryRepository, builder: ContextBuilder, llm, trigger_tokens: int):
        self.memory, self.builder, self.llm, self.trigger_tokens = (
            memory,
            builder,
            llm,
            trigger_tokens,
        )

    async def needs_summary(self, chat_id: int, thread_id: int | None) -> bool:
        messages = await self.memory.context_messages(chat_id, thread_id, limit=300)
        return self.builder.count_tokens("\n".join(m.text for m in messages)) >= self.trigger_tokens

    async def summarize(self, chat_id: int, thread_id: int | None) -> Summary | None:
        previous = await self.memory.latest_summary(chat_id, thread_id)
        messages = await self.memory.context_messages(chat_id, thread_id, limit=300)
        if not messages:
            return None
        context = self.builder.build(previous, messages)
        text = await self.llm.complete(
            [{"role": "user", "content": f"{SUMMARY_PROMPT}\n\n{context}"}]
        )
        summary = Summary(
            chat_id=chat_id,
            thread_id=thread_id,
            version=(previous.version if previous else 0) + 1,
            text=text,
            from_message_id=messages[0].telegram_message_id,
            to_message_id=messages[-1].telegram_message_id,
        )
        await self.memory.save_summary(summary)
        return summary