Add main.py

main.py

@@ -0,0 +1,127 @@
+"""Convert an informal assignment description into a validated flat card."""
+
+from __future__ import annotations
+
+import argparse
+import os
+
+from dotenv import find_dotenv, load_dotenv
+from langchain_core.output_parsers import PydanticOutputParser
+from langchain_core.prompts import PromptTemplate
+from langchain_openai import ChatOpenAI
+from pydantic import BaseModel, Field
+
+
+DEFAULT_DESCRIPTION = (
+    "Сдайте к пятнице мини-отчёт по LangChain: 2 страницы, упор на агентов. "
+    "Оценка: за полноту и за пример кода."
+)
+
+
+class AssignmentCard(BaseModel):
+    """Flat data card extracted from one assignment description."""
+
+    title: str = Field(..., description="Short title of the assignment")
+    subject: str = Field(..., description="Main topic or subject")
+    deadline_hint: str | None = Field(
+        None,
+        description="Deadline as a free-form phrase from the source text",
+    )
+    deliverable_type: str | None = Field(
+        None,
+        description="Expected deliverable: report, code, presentation, etc.",
+    )
+    grading_hints: list[str] = Field(
+        default_factory=list,
+        description="Assessment hints mentioned in the description",
+    )
+
+
+parser = PydanticOutputParser(pydantic_object=AssignmentCard)
+
+prompt = PromptTemplate(
+    template=(
+        "You convert one informal study assignment description into a flat "
+        "validated data card. Do not ask follow-up questions. Extract only "
+        "information supported by the input. If a field is not mentioned, use "
+        "null for optional strings or an empty list for grading_hints.\n\n"
+        "{format_instructions}\n\n"
+        "Assignment description:\n{description}"
+    ),
+    input_variables=["description"],
+    partial_variables={"format_instructions": parser.get_format_instructions()},
+)
+
+
+def build_llm() -> ChatOpenAI:
+    """Create an OpenAI-compatible chat model from environment variables."""
+
+    load_dotenv(find_dotenv(usecwd=True))
+    base_url = os.getenv("OPENAI_BASE_URL") or os.getenv("GPT2GIGA_BASE_URL")
+    api_key = os.getenv("OPENAI_API_KEY") or os.getenv("GPT2GIGA_OPENAI_API_KEY")
+    model = (
+        os.getenv("OPENAI_MODEL")
+        or os.getenv("GPT2GIGA_MODEL")
+        or "openai/gpt-oss-20b"
+    )
+    if not base_url:
+        raise RuntimeError("Set OPENAI_BASE_URL or GPT2GIGA_BASE_URL")
+    if not api_key:
+        raise RuntimeError("Set OPENAI_API_KEY or GPT2GIGA_OPENAI_API_KEY")
+
+    return ChatOpenAI(
+        model=model,
+        base_url=base_url,
+        api_key=api_key,
+        temperature=0,
+    )
+
+
+def parse_assignment(description: str) -> AssignmentCard:
+    """Run one prompt-model-parser chain and return a validated card."""
+
+    chain = prompt | build_llm() | parser
+    return chain.invoke({"description": description})
+
+
+def format_summary(card: AssignmentCard) -> str:
+    """Create a short human-readable summary from the validated card."""
+
+    grading = ", ".join(card.grading_hints) if card.grading_hints else "не указано"
+    return (
+        f"{card.title}: {card.deliverable_type or 'тип сдачи не указан'} "
+        f"по теме «{card.subject}». "
+        f"Срок: {card.deadline_hint or 'не указан'}. "
+        f"Критерии: {grading}."
+    )
+
+
+def print_card(card: AssignmentCard) -> None:
+    """Print both machine-friendly and human-friendly output."""
+
+    print("Validated object:")
+    for key, value in card.model_dump().items():
+        print(f"{key}: {value}")
+    print("\nSummary:")
+    print(format_summary(card))
+
+
+def main(argv: list[str] | None = None) -> AssignmentCard:
+    arg_parser = argparse.ArgumentParser(
+        description="Parse one raw assignment description into a flat card."
+    )
+    arg_parser.add_argument(
+        "description",
+        nargs="*",
+        help="One informal assignment description. Uses a sample if omitted.",
+    )
+    args = arg_parser.parse_args(argv)
+
+    description = " ".join(args.description).strip() or DEFAULT_DESCRIPTION
+    card = parse_assignment(description)
+    print_card(card)
+    return card
+
+
+if __name__ == "__main__":
+    main()