from pydantic import BaseModel, Field
from langchain_core.prompts import PromptTemplate
from langchain_openai import ChatOpenAI
from langchain_core.output_parsers import PydanticOutputParser

class TaskCard(BaseModel):
    title: str = Field(..., description="Title of the assignment")
    subject: str = Field(..., description="Subject or topic of the assignment")
    deadline_hint: str = Field(..., description="Free‑form hint about deadline")
    deliverable_type: str = Field(..., description="What is to be submitted (report, code, presentation, etc.)")
    grading_hints: list[str] = Field(..., description="List of hints mentioned about grading")

parser = PydanticOutputParser(pydantic_object=TaskCard)

prompt = PromptTemplate(
    template="""
You are an assistant that extracts structured information from a short assignment description.
Return the data in the following JSON format exactly:
{format_instructions}

Input: {input_text}
""",
    input_variables=["input_text"],
    partial_variables={"format_instructions": parser.get_format_instructions()},
)

llm = ChatOpenAI(temperature=0)
chain = prompt | llm | parser

if __name__ == "__main__":
    sample = "Сдайте к пятнице мини-отчёт по LangChain: 2 страницы, упор на агентов. Оценка: за полноту и за пример кода."
    result = chain.invoke({"input_text": sample})
    print("Parsed object:")
    print(result.model_dump())
    print("\nHuman readable summary:")
    print(f"Title: {result.title}\nSubject: {result.subject}\nDeadline: {result.deadline_hint}\nDeliverable: {result.deliverable_type}\nGrading hints: {', '.join(result.grading_hints)}")