[nit] Simplify Spark Creation Validation Check A Little Bit (#4761)

- simplify the validation check a little bit.
- re-tested in jupyter notebook.

Reviewer: @hwchase17

docs/modules/agents/toolkits/examples/spark.ipynb

@@ -1,6 +1,7 @@
 {
  "cells": [
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -17,7 +18,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.agents import create_spark_dataframe_agent\n",
     "import os\n",
     "\n",
     "os.environ[\"OPENAI_API_KEY\"] = \"...input your openai api key here...\""
@@ -25,9 +25,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "23/05/15 20:33:10 WARN Utils: Your hostname, Mikes-Mac-mini.local resolves to a loopback address: 127.0.0.1; using 192.168.68.115 instead (on interface en1)\n",
+      "23/05/15 20:33:10 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address\n",
+      "Setting default log level to \"WARN\".\n",
+      "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
+      "23/05/15 20:33:10 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -64,6 +75,7 @@
    "source": [
     "from langchain.llms import OpenAI\n",
     "from pyspark.sql import SparkSession\n",
+    "from langchain.agents import create_spark_dataframe_agent\n",
     "\n",
     "spark = SparkSession.builder.getOrCreate()\n",
     "csv_file_path = \"titanic.csv\"\n",
@@ -92,7 +104,7 @@
       "\n",
       "\n",
       "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
-      "\u001b[32;1m\u001b[1;3mThought: I need to find out the size of the dataframe\n",
+      "\u001b[32;1m\u001b[1;3mThought: I need to find out how many rows are in the dataframe\n",
       "Action: python_repl_ast\n",
       "Action Input: df.count()\u001b[0m\n",
       "Observation: \u001b[36;1m\u001b[1;3m891\u001b[0m\n",
@@ -205,7 +217,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -213,6 +225,7 @@
    ]
   },
   {
+   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [

langchain/agents/agent_toolkits/spark/base.py

@@ -14,9 +14,7 @@ def _validate_spark_df(df: Any) -> bool:
     try:
         from pyspark.sql import DataFrame as SparkLocalDataFrame
 
-        if not isinstance(df, SparkLocalDataFrame):
-            return False
-        return True
+        return isinstance(df, SparkLocalDataFrame)
     except ImportError:
         return False
 
@@ -25,9 +23,7 @@ def _validate_spark_connect_df(df: Any) -> bool:
     try:
         from pyspark.sql.connect.dataframe import DataFrame as SparkConnectDataFrame
 
-        if not isinstance(df, SparkConnectDataFrame):
-            return False
-        return True
+        return isinstance(df, SparkConnectDataFrame)
     except ImportError:
         return False