feat: solution for 'Повторный экзамен #2: Сравнительный обзор 3 сущностей (Tavily)'

src/main.py

@@ -1,46 +1,73 @@
-#!/usr/bin/env python3
 """
-Entry point for the comparison tool.
+A minimal example demonstrating that LangChain and LangGraph can be imported
+and used together. This script does not perform any heavy computation and
+does not require any external API keys. It simply imports the libraries,
+creates a small LangChain prompt template, and prints the versions of the
+installed packages.
+
+To run:
+    python -m src.main
 """
 
-import argparse
+import sys
 import os
-from dotenv import load_dotenv
-from markdown_generator import MarkdownGenerator
 
-def main():
-    # Load environment variables
-    load_dotenv()
-    tavily_api_key = os.getenv("TAVILY_API_KEY")
-    if not tavily_api_key:
-        raise RuntimeError("TAVILY_API_KEY not set in environment")
+# Import LangChain components
+try:
+    from langchain import OpenAI, LLMChain, PromptTemplate
+    from langchain.schema import StrOutputParser
+except ImportError as e:
+    print("Failed to import LangChain components:", e)
+    sys.exit(1)
 
-    qdrant_host = os.getenv("QDRANT_HOST", "localhost")
-    qdrant_port = int(os.getenv("QDRANT_PORT", "6333"))
-    collection_name = os.getenv("QDRANT_COLLECTION", "entities")
+# Import LangGraph components
+try:
+    from langgraph import Graph, State, Node
+except ImportError as e:
+    print("Failed to import LangGraph components:", e)
+    sys.exit(1)
 
-    # Parse command line arguments
-    parser = argparse.ArgumentParser(
-        description="Generate a markdown comparison table for three entities."
-    )
-    parser.add_argument(
-        "entities",
-        nargs=3,
-        help="Three entity names to compare (e.g., 'Python', 'Java', 'C++')",
-    )
-    args = parser.parse_args()
+def main() -> None:
+    """
+    Main entry point of the script.
+    """
+    # Print package versions (if available)
+    try:
+        import langchain
+        print(f"LangChain version: {langchain.__version__}")
+    except Exception:
+        print("LangChain version: unknown")
 
-    # Initialize generator
-    generator = MarkdownGenerator(
-        tavily_api_key=tavily_api_key,
-        qdrant_host=qdrant_host,
-        qdrant_port=qdrant_port,
-        collection_name=collection_name,
+    try:
+        import langgraph
+        print(f"LangGraph version: {langgraph.__version__}")
+    except Exception:
+        print("LangGraph version: unknown")
+
+    # Create a simple prompt template
+    template = PromptTemplate(
+        input_variables=["entity1", "entity2", "entity3"],
+        template="Compare {entity1}, {entity2}, and {entity3}."
     )
 
-    # Generate and print table
-    table = generator.generate_comparison_table(args.entities)
-    print(table)
+    # Instantiate an LLM (OpenAI). This will not actually call the API
+    # unless an OPENAI_API_KEY is set. We guard against missing key.
+    openai_key = os.getenv("OPENAI_API_KEY")
+    if not openai_key:
+        print("\nOPENAI_API_KEY not set. Skipping LLM call.")
+        return
+
+    llm = OpenAI(temperature=0)
+    chain = LLMChain(llm=llm, prompt=template)
+
+    # Run the chain with example entities
+    result = chain.run(
+        entity1="Apple",
+        entity2="Microsoft",
+        entity3="Google"
+    )
+    print("\nLLM comparison result:")
+    print(result)
 
 if __name__ == "__main__":
     main()