Add main.py

main.py

@@ -0,0 +1,36 @@
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import ChatOpenAI
+from pydantic import BaseModel, Field
+from typing import List
+
+class TaskCard(BaseModel):
+    title: str = Field(..., description="Task title")
+    subject: str | None = Field(None, description="Subject or topic of the task")
+    deadline_hint: str | None = Field(None, description="Short hint about deadline")
+    deliverable_type: str | None = Field(None, description="Type of deliverable (e.g., code, report)")
+    grading_hints: List[str] | None = Field(None, description="Hints for grading")
+
+prompt_template = ChatPromptTemplate.from_messages([
+    (
+        "system",
+        "You are an assistant that extracts structured task information from a raw text. Return JSON matching the TaskCard schema.",
+    ),
+    ("human", "{raw_text}"),
+])
+
+llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
+
+async def parse_task(raw_text: str) -> TaskCard:
+    chain = prompt_template | llm.with_structured_output(TaskCard)
+    result = await chain.ainvoke({"raw_text": raw_text})
+    return result
+
+if __name__ == "__main__":
+    import sys, json
+    if len(sys.argv) < 2:
+        print("Usage: python main.py <path_to_raw_task_file>")
+        sys.exit(1)
+    with open(sys.argv[1], "r", encoding="utf-8") as f:
+        raw = f.read()
+    card = asyncio.run(parse_task(raw))
+    print(json.dumps(card.model_dump(), indent=2))