38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
import os
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage
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from langchain_output_parsers import PydanticOutputParser
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from pydantic import BaseModel, Field
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class TaskCard(BaseModel):
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title: str = Field(..., description="Title of the task")
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subject: str = Field(..., description="Subject area")
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deadline_hint: str | None = Field(None, description="Hint about deadline")
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deliverable_type: str = Field(..., description="What to submit (report, code, etc.)")
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grading_hints: list[str] = Field(default_factory=list, description="Hints for grading")
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llm = ChatOpenAI(
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model="openai/gpt-oss-20b:free",
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base_url="https://openrouter.ai/api/v1",
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api_key=os.getenv("OPENAI_API_KEY"),
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temperature=0.0,
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)
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parser = PydanticOutputParser(pydantic_object=TaskCard)
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prompt_template = """
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You are a task summarizer.
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Given the following informal description of an assignment, produce a JSON object matching TaskCard model.
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Description: {description}
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{format_instructions}
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"""
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prompt = prompt_template | llm | parser
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async def main():
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description = "Сдайте к пятнице мини-отчёт по LangChain: 2 страницы, упор на агентов. Оценка: за полноту и за пример кода."
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result = await prompt.ainvoke({"description": description})
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print(result["messages"][-1].content)
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if __name__ == "__main__":
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import asyncio
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asyncio.run(main())
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