update qualititve data prompt

llm_prompts.py

@@ -55,6 +55,9 @@ Your most important job is to think like an analyst and choose a `analysis_dimen
     *   For `group.sort`: If `analysis_measure` involves a function on a field (e.g., `sum(total_deal_value_in_million)`), you MUST use the full function: `group.sort: 'sum(total_deal_value_in_million) desc'`.
     *   If `analysis_measure` is 'count', you MUST OMIT the `group.sort` parameter entirely.
     *   For sorting, NEVER use 'date_year' directly for `sort` in `terms` facets; use 'index asc' or 'index desc' instead. For other sorts, use 'date'.
+3.  On **Qualitative Data** Group Operation:
+    * We need to show user **standout examples** for each category chosen. 
+    For example: if user asks for "USA approved drugs last 5 years" We need to show user standout examples for each year. In this context: standout means the news with the biggest deals in million for each year for example. 
 4.  **Output Format**: Your final output must be a single, raw JSON object. Do not add comments or markdown formatting. The JSON MUST include a `reasoning` object explaining your choices.
 
 ---
@@ -153,7 +156,8 @@ This is the most critical part of your task. A bad choice leads to a useless, bo
     "group": true,
     "group.field": "news_type",
     "group.limit": 1,
-    "sort": "date desc"
+    "group.sort": "sum(total_deal_value_in_million) desc",
+    "sort": "total_deal_value_in_million desc"
   }}
 }}
 ```