wip

mariofusco · mariofusco · commit 789b399f628a · 2025-05-09T11:21:58.000+02:00
diff --git a/_posts/2025-05-08-agentic-ai-with-quarkus-p3.adoc b/_posts/2025-05-08-agentic-ai-with-quarkus-p3.adoc
@@ -77,7 +77,7 @@ public interface ExpertsSelectorAgent {
 }
 ----
 
-The `@ToolBox` annotation is used to specify the list of tools the agent can use, in this case, the three experts. Note that, similarly to what has been done for other agentic examples in the previous post of this series, this AI service has been configured to use a model capable of reasoning and requesting tool invocations. In our example, the model is configured in the `application.properties` file and is using  `qwen2.5` with 7 billion parameters.
+The `@ToolBox` annotation is used to specify the list of tools the agent can use, in this case, the three experts. Note that, similarly to what has been done for other agentic examples in the previous post of this series, this AI service has been configured to use a model capable of reasoning and requesting tool invocations. In our example, the model is configured in the `application.properties` file and is using  `qwen2.5` with 7 billion parameters. In addition, the `temperature` is set to 0 to make the classification more predictable and minimize the possibility of hallucinations.
 
 [source,properties]
 ----

Original file line number	Diff line number	Diff line change
`@@ -77,7 +77,7 @@ public interface ExpertsSelectorAgent {`
`77`	`77`	`}`
`78`	`78`	`----`
`79`	`79`
`80`		-The `@ToolBox` annotation is used to specify the list of tools the agent can use, in this case, the three experts. Note that, similarly to what has been done for other agentic examples in the previous post of this series, this AI service has been configured to use a model capable of reasoning and requesting tool invocations. In our example, the model is configured in the `application.properties` file and is using `qwen2.5` with 7 billion parameters.
	`80`	+The `@ToolBox` annotation is used to specify the list of tools the agent can use, in this case, the three experts. Note that, similarly to what has been done for other agentic examples in the previous post of this series, this AI service has been configured to use a model capable of reasoning and requesting tool invocations. In our example, the model is configured in the `application.properties` file and is using `qwen2.5` with 7 billion parameters. In addition, the `temperature` is set to 0 to make the classification more predictable and minimize the possibility of hallucinations.
`81`	`81`
`82`	`82`	`[source,properties]`
`83`	`83`	`----`