add file

main.py

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+from pydantic import BaseModel, Field
+from typing import List
+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 deadline hint")
+    deliverable_type: str = Field(..., description="What to submit: report, code, presentation, etc.")
+    grading_hints: List[str] = Field(..., description="List of grading hints mentioned in the text")
+
+parser = PydanticOutputParser(pydantic_object=TaskCard)
+
+prompt_template = (
+    "You are an assistant that extracts structured information from a short assignment description. "
+    "Return the data in the following JSON format exactly as required by the parser. "
+    "Do not add any extra keys or text.\n"
+    "{format_instructions}\n"
+    "Input: {input_text}\n"
+    "Output:"
+)
+
+prompt = PromptTemplate(
+    template=prompt_template,
+    input_variables=["input_text"],
+    partial_variables={"format_instructions": parser.get_format_instructions()},
+)
+
+llm = ChatOpenAI(temperature=0)
+
+chain = prompt | llm | parser
+
+if __name__ == "__main__":
+    # Example input
+    input_text = "Сдайте к пятнице мини-отчёт по LangChain: 2 страницы, упор на агентов. Оценка: за полноту и за пример кода."
+    result = chain.invoke({"input_text": input_text})
+    print("Parsed object:")
+    print(result.model_dump())
+    print("\nHuman readable summary:\n")
+    print(f"Title: {result.title}")
+    print(f"Subject: {result.subject}")
+    print(f"Deadline: {result.deadline_hint}")
+    print(f"Deliverable: {result.deliverable_type}")
+    print(f"Grading hints: {', '.join(result.grading_hints)}")