Update README.md

README.md

@@ -109,11 +109,20 @@ That order matters. Weak personas produce fluent but empty outputs. Stronger per
 ```python
 from datasets import load_dataset
 
+# Load the dataset
 ds = load_dataset("Meddies/meddies-persona-vie", split="train")
+p = ds[0]
 
-print(ds)
-print(ds[0].keys())
-print(ds[0]["demographics"])
+# Injecting the persona into an LLM prompt
+system_prompt = f"""
+Act as a Vietnamese primary care doctor. Adapt your vocabulary to this patient:
+
+- Patient: {p['demographics']['full_name']} ({p['demographics']['gender']}, {p['demographics']['province']})
+- Background: {p['socioeconomic']['occupation']} (Health literacy: {p['healthcare_behavior']['health_literacy_level']})
+- Chief Complaint: "{p['llm_fields']['chief_complaint']}"
+"""
+
+print(system_prompt)
 ```
 
 ## Good fits