Add logging in PBI tool (#5841)

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Add some logging into the powerbi tool so that you can see the queries
being sent to PBI and attempts to correct them.

<!-- Remove if not applicable -->

Fixes # (issue)

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Tag maintainers/contributors who might be interested: @vowelparrot 

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langchain/tools/powerbi/tool.py

@@ -1,4 +1,5 @@
 """Tools for interacting with a Power BI dataset."""
+import logging
 from typing import Any, Dict, Optional, Tuple
 
 from pydantic import Field, validator
@@ -17,6 +18,8 @@ from langchain.tools.powerbi.prompt import (
 )
 from langchain.utilities.powerbi import PowerBIDataset, json_to_md
 
+logger = logging.getLogger(__name__)
+
 
 class QueryPowerBITool(BaseTool):
     """Tool for querying a Power BI Dataset."""
@@ -73,9 +76,11 @@ class QueryPowerBITool(BaseTool):
     ) -> str:
         """Execute the query, return the results or an error message."""
         if cache := self._check_cache(tool_input):
+            logger.debug("Found cached result for %s: %s", tool_input, cache)
             return cache
 
         try:
+            logger.info("Running PBI Query Tool with input: %s", tool_input)
             query = self.llm_chain.predict(
                 tool_input=tool_input,
                 tables=self.powerbi.get_table_names(),
@@ -88,6 +93,7 @@ class QueryPowerBITool(BaseTool):
         if query == "I cannot answer this":
             self.session_cache[tool_input] = query
             return self.session_cache[tool_input]
+        logger.info("Query: %s", query)
         pbi_result = self.powerbi.run(command=query)
         result, error = self._parse_output(pbi_result)
 
@@ -114,8 +120,10 @@ class QueryPowerBITool(BaseTool):
     ) -> str:
         """Execute the query, return the results or an error message."""
         if cache := self._check_cache(tool_input):
+            logger.debug("Found cached result for %s: %s", tool_input, cache)
             return cache
         try:
+            logger.info("Running PBI Query Tool with input: %s", tool_input)
             query = await self.llm_chain.apredict(
                 tool_input=tool_input,
                 tables=self.powerbi.get_table_names(),
@@ -129,6 +137,7 @@ class QueryPowerBITool(BaseTool):
         if query == "I cannot answer this":
             self.session_cache[tool_input] = query
             return self.session_cache[tool_input]
+        logger.info("Query: %s", query)
         pbi_result = await self.powerbi.arun(command=query)
         result, error = self._parse_output(pbi_result)