37 lines
1.7 KiB
Python
37 lines
1.7 KiB
Python
from pydantic import BaseModel, Field
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from langchain_core.prompts import PromptTemplate
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from langchain_openai import ChatOpenAI
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from langchain_core.output_parsers import PydanticOutputParser
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class TaskCard(BaseModel):
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title: str = Field(..., description="Title of the assignment")
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subject: str = Field(..., description="Subject or topic of the assignment")
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deadline_hint: str = Field(..., description="Free‑form hint about deadline")
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deliverable_type: str = Field(..., description="What is to be submitted (report, code, presentation, etc.)")
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grading_hints: list[str] = Field(..., description="List of hints mentioned about grading")
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parser = PydanticOutputParser(pydantic_object=TaskCard)
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prompt = PromptTemplate(
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template="""
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You are an assistant that extracts structured information from a short assignment description.
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Return the data in the following JSON format exactly:
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{format_instructions}
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Input: {input_text}
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""",
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input_variables=["input_text"],
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partial_variables={"format_instructions": parser.get_format_instructions()},
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)
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llm = ChatOpenAI(temperature=0)
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chain = prompt | llm | parser
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if __name__ == "__main__":
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sample = "Сдайте к пятнице мини-отчёт по LangChain: 2 страницы, упор на агентов. Оценка: за полноту и за пример кода."
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result = chain.invoke({"input_text": sample})
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print("Parsed object:")
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print(result.model_dump())
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print("\nHuman readable summary:")
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print(f"Title: {result.title}\nSubject: {result.subject}\nDeadline: {result.deadline_hint}\nDeliverable: {result.deliverable_type}\nGrading hints: {', '.join(result.grading_hints)}")
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