import os
from langchain_openai import ChatOpenAI
from langchain_core.prompts import PromptTemplate
from langchain.output_parsers import PydanticOutputParser
from models import TaskCard
from typing import List

class TaskParser:
    """Converts raw task text into a TaskCard using LangChain."""

    def __init__(self) -> None:
        self.llm = ChatOpenAI(
            model="openai/gpt-oss-20b:free",
            base_url="https://platform.brojs.ru/jrnl-bh/api/inference/v1",
            api_key=os.getenv("JOURNAL_MCP_PAT"),
            temperature=0.0,
        )
        self.output_parser = PydanticOutputParser(pydantic_object=TaskCard)
        self.prompt = PromptTemplate(
            template=(
                "Parse the following raw task description into a structured card.\n"
                "{format_instructions}\n\nRaw text:\n{raw_text}\n\nJSON:"
            ),
            input_variables=["raw_text"],
            partial_variables={"format_instructions": self.output_parser.get_format_instructions()},
        )
        self.chain = self.prompt | self.llm | self.output_parser

    def parse(self, raw_text: str) -> TaskCard:
        """Parse a single raw task description."""
        return self.chain.invoke({"raw_text": raw_text})

    def batch_parse(self, texts: List[str]) -> List[TaskCard]:
        """Parse multiple raw task descriptions."""
        return [self.parse(t) for t in texts]