add the llm gateway testing comment in readme

Author: atulikumwenayo

README.md

@@ -305,6 +305,53 @@ Options:
 - `--function-invoke-opt TEXT`: Currently we support only `UnstructuredChunking` for functions.
 
 
+## Testing LLM Gateway
+
+You can use AI models configured in Salesforce to generate responses while transforming your data. Below is a sample code example:
+
+```
+from datacustomcode.client import Client, llm_gateway_generate_text_col
+
+
+def main():
+  client = Client()
+  df = client.read_dlo("Input__dll")
+  df_generated = df.withColumn(
+    "greeting__c",
+    llm_gateway_generate_text_col(
+        "In one sentence, greet {name} from {city}.",
+        {"name": col("name__c"), "city": col("homecity__c")},
+        model_id="sfdc_ai__DefaultGPT4Omni", # An AI model in your org
+        max_tokens=100,
+    ),
+  )
+
+  dlo_name = "Output_dll"
+  client.write_to_dlo(dlo_name, df_upper1, write_mode=WriteMode.APPEND)
+
+  greeting = client.llm_gateway_generate_text("In one sentence, generate a greeting message", "sfdc_ai__DefaultGPT52")
+
+if __name__ == "__main__":
+  main()
+```
+
+In order to test this code on your local machine before deploying it to Data Cloud, you must first set up an External Client App that allows access to the Agent API. Follow this guide to create the ECA https://developer.salesforce.com/docs/ai/agentforce/guide/agent-api-get-started.html#create-a-salesforce-app. You must use `http://localhost:1717/OauthRedirect` as the callback URL.
+
+Once the ECA is set up, log in to your org using this ECA
+```
+sf org login web \
+  --alias myorg \
+  --instance-url https://{MY_DOMAIN_URL} \
+  --client-id {CONSUMER_KEY} \
+  --scopes "sfap_api api"
+```
+
+then you can test your code using `myorg` alias
+```
+datacustomcode run ./payload/entrypoint.py --sf-cli-org myorg
+```
+
+
 ## Docker usage
 
 The SDK provides Docker-based development options that allow you to test your code in an environment that closely resembles Data Cloud's execution environment.

src/datacustomcode/templates/function/example/chunking_with_llm/entrypoint.py

@@ -9,12 +9,7 @@
 - Automatic validation and conversion
 
 You can use your AI models configured in Salesforce to generate texts.
-
-For testing locally before deploying your code to Data Cloud
-(``datacustomcode run``), first configure an external client app before using
-LLM functionality, then configure the SDK with your client app credentials.
-
-https://developer.salesforce.com/docs/ai/agentforce/guide/agent-api-get-started.html#create-a-salesforce-app
+See README.md for how to test locally before deploying to Data Cloud.
 """
 
 import logging

src/datacustomcode/templates/function/example/chunking_with_prediction/entrypoint.py

@@ -14,12 +14,7 @@
 Output: Predicted_SalePrice
 
 You can use your AI models configured in Salesforce to make predictions.
-
-For testing locally before deploying your code to Data Cloud
-(``datacustomcode run``), first configure an external client app before using
-LLM functionality, then configure the SDK with your client app credentials.
-
-https://developer.salesforce.com/docs/ai/agentforce/guide/agent-api-get-started.html#create-a-salesforce-app
+See README.md for how to test locally before deploying to Data Cloud.
 """
 
 import logging

src/datacustomcode/templates/function/payload/entrypoint.py

@@ -85,14 +85,8 @@ def function(request: dict, runtime: Runtime) -> dict:
 
     """
     You can use your AI models configured in Salesforce to generate texts
-    or predict an outcome.
-
-    For testing locally before deploying your code to Data Cloud
-    (``datacustomcode run``), first configure an external client app before
-    using LLM functionality, then configure the SDK with your client app
-    credentials.
-
-    https://developer.salesforce.com/docs/ai/agentforce/guide/agent-api-get-started.html#create-a-salesforce-app
+    or predict an outcome. See README.md for how to test locally before
+    deploying to Data Cloud.
 
     Example:
 

src/datacustomcode/templates/script/payload/entrypoint.py

@@ -14,12 +14,7 @@ def main():
 
     """
     You can use your AI models configured in Salesforce to generate column
-    values. For testing locally before deploying your code to Data Cloud
-    (``datacustomcode run``), first configure an external client app before
-    using LLM functionality, then configure the SDK with your client app
-    credentials.
-
-    https://developer.salesforce.com/docs/ai/agentforce/guide/agent-api-get-started.html#create-a-salesforce-app
+    values. See README.md for how to test locally before deploying to Data Cloud.
 
     Example: