Update helper.py

helper.py

@@ -232,23 +232,16 @@ from langchain_community.tools import WikipediaQueryRun
 from langchain_community.utilities import WikipediaAPIWrapper
 from langchain.tools import Tool # Ensure Tool is imported
 
+
 def get_wikipedia_tool() -> Tool:
     """
     Creates and returns a LangChain Tool for querying Wikipedia.
     """
-    # Initialize the Wikipedia API Wrapper
-    # Configure the wrapper to control how much content is returned.
-    # 'top_k_results': Number of search results to return.
-    # 'doc_content_chars_max': Maximum number of characters from the page content.
-    #                        Setting this to a reasonable limit (e.g., 2000-4000)
-    #                        is crucial for token management, as Wikipedia articles can be very long.
-    #                        Adjust based on your LLM's context window and typical use cases.
     wikipedia_api_wrapper = WikipediaAPIWrapper(
-        top_k_results=3,             # Get up to 3 most relevant articles
-        doc_content_chars_max=2000   # Limit content to 2000 characters per article
+        top_k_results=3,
+        doc_content_chars_max=2000
     )
 
-    # Initialize the Wikipedia tool with the wrapper
     wikipedia_query_tool = WikipediaQueryRun(api_wrapper=wikipedia_api_wrapper)
 
     return Tool(
@@ -277,7 +270,7 @@ def get_wikipedia_tool() -> Tool:
         **Output:**
         The tool returns a string containing snippets of relevant Wikipedia articles.
         The output is limited in length to save tokens. If the answer is not found in the snippet,
-        you might need to refine your query or consider using a broader search tool like 'tavily_search'.
+        you might need to refine your query or **consider using 'tavily_search' or other available tools for a broader search.**
         """,
         func=wikipedia_query_tool.run,
     )