Update llms.mdx

docs/llms.mdx

@@ -7,11 +7,11 @@ The generated code is then executed to produce the result.
 
 [![Choose the LLM](https://cdn.loom.com/sessions/thumbnails/5496c9c07ee04f69bfef1bc2359cd591-00001.jpg)](https://www.loom.com/share/5496c9c07ee04f69bfef1bc2359cd591 "Choose the LLM")
 
-You can either choose a LLM by instantiating one and passing it to the `SmartDataFrame` or `SmartDatalake` constructor,
-or you can specify one in the `pandasai.json` file.
+You can either choose a LLM by either instantiating it and passing it to the `SmartDataFrame` or `SmartDatalake` constructor,
+or by specifying it in the `pandasai.json` configuration file.
 
 If the model expects one or more parameters, you can pass them to the constructor or specify them in the `pandasai.json`
-file, in the `llm_options` param, as it follows:
+file, in the `llm_options` parameters, Here’s an example of how to structure your `pandasai.json` file:
 
 ```json
 {
@@ -21,6 +21,24 @@ file, in the `llm_options` param, as it follows:
   }
 }
 ```
+> **Note:** 
+> `pandasai.json` can be configure for any LLM.
+
+## Working with pandasai.json file
+
+In this example, `data.csv` is your data file, and pandasai.json is the configuration file. Make sure the configuration file is named `pandasai.json` and is in the same folder as your code.
+
+```python
+from pandasai import SmartDataframe
+from pandasai.config import load_config_from_json
+
+# Load configuration from pandasai.json
+config = load_config_from_json()
+
+df = SmartDataframe("data.csv", config=config)
+response = df.chat("give me revenue of Top 5 companies for year 2021")
+print(response)
+```
 
 ## BambooLLM