import os
import json
from typing import List
from langchain_openai import ChatOpenAI
from langchain_core.output_parsers import JsonOutputParser
from langchain_core.prompts import PromptTemplate
from pydantic import BaseModel

from models import TaskCard

class TaskParser:
    """Parser that converts raw task descriptions into TaskCard objects using a LLM."""

    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=0.1,
        )
        self.parser = JsonOutputParser(pydantic_object=TaskCard)
        self.prompt = PromptTemplate(
            input_variables=["raw_text"],
            template="""
Parse the following raw task description into a JSON object matching the TaskCard schema.
The output must be valid JSON and contain all required fields.
If a field cannot be determined, use null for optional fields or an empty list for lists.

Raw text:
{raw_text}

JSON output:
""",
        )

    def _run_llm(self, raw_text: str) -> TaskCard:
        chain = self.prompt | self.llm | self.parser
        return chain.invoke({"raw_text": raw_text})

    def parse(self, raw_text: str) -> TaskCard:
        return self._run_llm(raw_text)

    def batch_parse(self, texts: List[str]) -> List[TaskCard]:
        return [self.parse(t) for t in texts]

    def save_to_file(self, card: TaskCard, filename: str) -> None:
        with open(filename, "w", encoding="utf-8") as f:
            json.dump(card.dict(), f, ensure_ascii=False, indent=2)

# End of parser.py