From aee33d81dbc5bccde2bb3bee28acc11b01ffa6b9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=9A=D0=B8=D1=80=D0=B8=D0=BB=D0=BB=20=D0=9A=D1=83=D1=82?=
 =?UTF-8?q?=D0=BB=D0=B0=D1=85=D0=BC=D0=B5=D1=82=D0=BE=D0=B2?=
 <kirillkutlahmetov10@gmail.com>
Date: Wed, 27 May 2026 14:04:34 +0000
Subject: [PATCH] add main.py

---
 main.py | 70 +++++++++++++++++++++++++++++++++++++++++++++------------
 1 file changed, 56 insertions(+), 14 deletions(-)

diff --git a/main.py b/main.py
index d350b9a..587e0eb 100644
--- a/main.py
+++ b/main.py
@@ -1,25 +1,67 @@
 import os
 import json
+from dotenv import load_dotenv
+from models import TaskCard
 from parser import TaskParser
 
-# Example raw texts
-RAW_TEXTS = [
-    "Напишите мини-отчёт по LangChain до пятницы, 3-5 страниц, критерии: полнота и примеры кода",
-    "Сделать агента на LangGraph который умеет искать в интернете, сдать ссылку на github",
-    "Реализовать REST API на FastAPI с авторизацией JWT, покрыть тестами, дедлайн 1 июня",
+load_dotenv()
+
+# Example raw task descriptions
+EXAMPLES = [
+    "Write a mini-report on LangChain for Friday, 3-5 pages, include code examples",
+    "Build a LangGraph agent with memory and interrupts, push code to github by Monday",
+    "Implement a REST API with FastAPI and JWT auth, add unit tests, deadline in 1 week",
+    "Create a RAG pipeline using Qdrant vector store and OpenAI embeddings",
+    "Build a chat bot with multi-turn memory using LangChain ConversationBufferMemory",
 ]
 
+def demo_single(parser: TaskParser, text: str, idx: int) -> TaskCard:
+    """Parse one example and print result."""
+    print(f"\n=== Example {idx} ===")
+    print(f"Raw: {text[:80]}")
+    card = parser.parse(text)
+    print(card.to_markdown())
+    return card
+
+def demo_batch(parser: TaskParser, texts: list) -> list:
+    """Parse a batch of texts and save as JSON."""
+    print("\n=== Batch parse ===")
+    cards = parser.batch_parse(texts)
+    for i, card in enumerate(cards):
+        fname = f"card_{i+1}.json"
+        with open(fname, "w", encoding="utf-8") as f:
+            json.dump(card.model_dump(), f, ensure_ascii=False, indent=2)
+        print(f"  Saved {fname}: {card.title}")
+    return cards
+
+def demo_format(card: TaskCard) -> None:
+    """Demonstrate different output formats."""
+    print("\n=== Formats ===")
+    print("Markdown:")
+    print(card.to_markdown())
+    print("\nJSON:")
+    print(json.dumps(card.model_dump(), ensure_ascii=False, indent=2))
+
 def main() -> None:
+    """Run all demos."""
     parser = TaskParser()
-    cards = parser.batch_parse(RAW_TEXTS)
-    for idx, card in enumerate(cards, start=1):
-        print(f"\n=== Task {idx} ===")
-        print(card.to_markdown())
-        filename = f"task_{idx}.json"
-        parser.save_to_file(card, filename)
-        print(f"Saved to {filename}")
+
+    # Demo 1: single parse
+    card1 = demo_single(parser, EXAMPLES[0], 1)
+
+    # Demo 2: another single parse
+    demo_single(parser, EXAMPLES[1], 2)
+
+    # Demo 3: third single parse
+    demo_single(parser, EXAMPLES[2], 3)
+
+    # Demo 4: batch parse all examples
+    demo_batch(parser, EXAMPLES)
+
+    # Demo 5: show formats
+    demo_format(card1)
+
+    print("\nDone!")
 
 if __name__ == "__main__":
     main()
-
-# End of main.py