From 482a0ae2c61887a24b6ba3232b2249233f9e9d95 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=A0=D0=B8=D0=BD=D0=B0=D1=80=20=D0=9C=D0=B8=D1=80=D0=B7?=
 =?UTF-8?q?=D0=B0=D0=B3=D0=B8=D1=82=D0=BE=D0=B2?= <mirzagitov03@mail.ru>
Date: Thu, 28 May 2026 08:41:44 +0000
Subject: [PATCH] Remove extra main.py

---
 main.py | 63 ---------------------------------------------------------
 1 file changed, 63 deletions(-)
 delete mode 100644 main.py

diff --git a/main.py b/main.py
deleted file mode 100644
index c099298..0000000
--- a/main.py
+++ /dev/null
@@ -1,63 +0,0 @@
-"""
-Simple module that converts informal assignment description into a structured data card.
-
-Usage:
-    from main import parse_assignment
-    card = parse_assignment("Write an essay on climate change by next Friday")
-"""
-from typing import Dict, Any
-
-from langchain.output_parsers import PydanticOutputParser
-from pydantic import BaseModel, Field
-
-class AssignmentCard(BaseModel):
-    title: str = Field(..., description="Short title of the assignment")
-    subject: str | None = Field(None, description="Subject or topic of the assignment")
-    deadline_hint: str | None = Field(
-        None,
-        description="Human‑readable hint about when the assignment is due",
-    )
-    deliverable_type: str | None = Field(
-        None,
-        description="What kind of work should be submitted (essay, report, code, etc.)",
-    )
-    grading_hints: str | None = Field(
-        None,
-        description="Any hints about how the assignment will be graded",
-    )
-
-parser = PydanticOutputParser(pydantic_object=AssignmentCard)
-
-# Prompt template that asks the model to output JSON matching AssignmentCard
-PROMPT_TEMPLATE = (
-    "You are an assistant that converts a short informal description of a study assignment into a structured data card."
-    " Return only valid JSON that matches the following schema:\n{schema}\n"
-    " Description: {description}"
-)
-
-def parse_assignment(description: str) -> AssignmentCard:
-    """Return an AssignmentCard parsed from the given description.
-
-    The function uses LangChain's PydanticOutputParser to enforce type safety.
-    """
-    from langchain import PromptTemplate, LLMChain
-    from langchain.chat_models import ChatOpenAI
-
-    # Use a small model for demonstration; replace with your own key if needed.
-    llm = ChatOpenAI(temperature=0.2)
-    prompt = PromptTemplate(
-        input_variables=["description", "schema"],
-        template=PROMPT_TEMPLATE,
-    )
-    chain = LLMChain(llm=llm, prompt=prompt, output_parser=parser)
-    result = chain.run(description=description, schema=parser.get_format_instructions())
-    return result
-
-if __name__ == "__main__":
-    import sys
-    if len(sys.argv) < 2:
-        print("Usage: python main.py '<assignment description>'")
-        sys.exit(1)
-    desc = sys.argv[1]
-    card = parse_assignment(desc)
-    print(card.json(indent=4))