compact doc

docs/utility_function/llm.md

@@ -77,7 +77,6 @@ class SummarizeNode(Node):
         return call_llm(f"Summarize: {text}", self.cur_retry==0)
 ```
 
-
 - Enable logging:
 
 ```python
@@ -93,4 +92,4 @@ def call_llm(prompt):
 I believe it is a **bad practice** to provide LLM-specific implementations in a general framework:
 - **LLM APIs change frequently**. Hardcoding them makes maintenance a nightmare.
 - You may need **flexibility** to switch vendors, use fine-tuned models, or deploy local LLMs.
-- You may need **optimizations** like prompt caching, request batching, or response streaming.
+- You may need **optimizations** like prompt caching, request batching, or response streaming.

docs/utility_function/tool.md

@@ -68,7 +68,6 @@ def execute_sql(query):
     return result
 ```
 
-
 > ⚠️ Beware of SQL injection risk
 {: .warning }
 

docs/utility_function/viz.md

@@ -137,6 +137,4 @@ data_science_flow = DataScienceFlow(start=data_prep_node)
 data_science_flow.run({})
 ```
 
-The output would be: `Call stack: ['EvaluateModelNode', 'ModelFlow', 'DataScienceFlow']`
-
-
+The output would be: `Call stack: ['EvaluateModelNode', 'ModelFlow', 'DataScienceFlow']`