diff --git a/README.md b/README.md
index a9bb58f97..d12b5a9eb 100644
--- a/README.md
+++ b/README.md
@@ -47,7 +47,7 @@ from pandasai.llm.openai import OpenAI
 llm = OpenAI(api_token="YOUR_API_TOKEN")
 
 pandas_ai = PandasAI(llm, conversational=False)
-pandas_ai.run(df, prompt='Which are the 5 happiest countries?')
+pandas_ai(df, prompt='Which are the 5 happiest countries?')
 ```
 
 The above code will return the following:
@@ -64,7 +64,7 @@ Name: country, dtype: object
 Of course, you can also ask PandasAI to perform more complex queries. For example, you can ask PandasAI to find the sum of the GDPs of the 2 unhappiest countries:
 
 ```python
-pandas_ai.run(df, prompt='What is the sum of the GDPs of the 2 unhappiest countries?')
+pandas_ai(df, prompt='What is the sum of the GDPs of the 2 unhappiest countries?')
 ```
 
 The above code will return the following:
@@ -76,7 +76,7 @@ The above code will return the following:
 You can also ask PandasAI to draw a graph:
 
 ```python
-pandas_ai.run(
+pandas_ai(
     df,
     "Plot the histogram of countries showing for each the gpd, using different colors for each bar",
 )
diff --git a/pandasai/__init__.py b/pandasai/__init__.py
index 42535dc03..545de10b5 100644
--- a/pandasai/__init__.py
+++ b/pandasai/__init__.py
@@ -170,6 +170,25 @@ def run(
             self.log(f"Conversational answer: {answer}")
         return answer
 
+    def __call__(
+        self,
+        data_frame: pd.DataFrame,
+        prompt: str,
+        is_conversational_answer: bool = None,
+        show_code: bool = False,
+        anonymize_df: bool = True,
+        use_error_correction_framework: bool = True,
+    ) -> str:
+        """Run the LLM with the given prompt"""
+        return self.run(
+            data_frame,
+            prompt,
+            is_conversational_answer,
+            show_code,
+            anonymize_df,
+            use_error_correction_framework
+        )
+
     def remove_unsafe_imports(self, code: str) -> str:
         """Remove non-whitelisted imports from the code to prevent malicious code execution"""