Update app.py

app.py

@@ -81,6 +81,47 @@ def process_records_gradio(records, example_records, fields, question):
     except Exception as e:
         return f"Error: {str(e)}"
 
+description = """
+Enter JSON data for `rg.Record.to_dict()`, `List[rg.Record.to_dict()]`, `List[Field].serialize()`, or `List[rg.Question.serialize()]` At least one of fields or question must be provided.
+
+```python
+import json
+import os
+from gradio_client import Client
+
+import argilla as rg
+
+# Initialize Argilla client
+client = rg.Argilla(
+    api_key=os.environ["ARGILLA_API_KEY"], api_url=os.environ["ARGILLA_API_URL"]
+)
+
+# Load the dataset
+dataset = client.datasets(name="my_dataset", workspace="my_workspace")
+
+# Prepare example data
+example_field = dataset.settings.fields["my_input_field"].serialize()
+example_question = dataset.settings.questions["my_question_to_predict"].serialize()
+
+payload = {
+    "records": [next(dataset.records()).to_dict()],
+    "fields": [example_field],
+    "question": example_question,
+}
+
+# Use gradio client to process the data
+client = Client("davidberenstein1957/distilabel-argilla-labeller")
+
+result = client.predict(
+    records=json.dumps(payload["records"]),
+    example_records=json.dumps(payload["example_records"]),
+    fields=json.dumps(payload["fields"]),
+    question=json.dumps(payload["question"]),
+    api_name="/predict"
+)
+
+```
+"""
 
 interface = gr.Interface(
     fn=process_records_gradio,
@@ -92,8 +133,8 @@ interface = gr.Interface(
     ],
     examples=examples,
     outputs=gr.Code(label="Suggestions", language="json", lines=10),
-    title="Record Processing Interface",
-    description="Enter JSON data for `rg.Record.to_dict()`, `List[rg.Record.to_dict()]`, `List[Field].serialize()`, or `List[rg.Question.serialize()]` At least one of fields or question must be provided.",
+    title="Distilabel - ArgillaLabeller - Record Processing Interface",
+    description=description,
 )
 
 if __name__ == "__main__":