Refactor DocumentationTool for improved logging and search request handling

src/main/java/com/olympus/hermione/services/ScenarioExecutionService.java

@@ -441,18 +441,12 @@ public class ScenarioExecutionService {
                 AzureOpenAiChatOptions.Builder optionsBuilder = AzureOpenAiChatOptions.builder()
                     .deploymentName(aiModel.getModel());
                 
-                // Aggiungi maxTokens solo se non è nullo
+                if (aiModel.isLegacy() ) {
-                if (aiModel.getMaxTokens() != null) {
+                    logger.info("Using legacy Azure OpenAI model: " + aiModel.getModel());
+                    optionsBuilder.temperature(aiModel.getTemperature().doubleValue());
                     optionsBuilder.maxTokens(aiModel.getMaxTokens());
-                    logger.info("Setting maxTokens: " + aiModel.getMaxTokens());
+                } 
-                }
+
-                
-                // Aggiungi temperature solo se non è nullo
-                if (aiModel.getTemperature() != null) {
-                    optionsBuilder.temperature(Double.valueOf(aiModel.getTemperature()));
-                    logger.info("Setting temperature: " + aiModel.getTemperature());
-                }
-                
                 AzureOpenAiChatOptions openAIChatOptions = optionsBuilder.build();
 
 

src/main/java/com/olympus/hermione/tools/DocumentationTool.java

@@ -13,52 +13,107 @@ import org.springframework.ai.vectorstore.VectorStore;
 
 public class DocumentationTool {
 
-    Logger logger = Logger.getLogger(DocumentationTool.class.getName());
+   private static final Logger logger = Logger.getLogger(DocumentationTool.class.getName());
-
+    private static final int DEFAULT_TOP_K = 5;
-    private String application;
+    private static final double DEFAULT_SIMILARITY_THRESHOLD = 0.7;
-    private String project;
-    private VectorStore vectorStore;
 
+    private final String application;
+    private final String project;
+    private final VectorStore vectorStore;
 
+    /**
+     * Costruttore per DocumentationTool.
+     * 
+     * @param application Nome dell'applicazione
+     * @param project Nome del progetto
+     * @param vectorStore Vector store contenente i documenti
+     */
     public DocumentationTool(String application, String project, VectorStore vectorStore) {
         this.application = application;
         this.project = project;
         this.vectorStore = vectorStore;
     }
      
-    @Tool(description = "Find any functional information about the application. Can be used to answeer any questron with a specific focus on the application")
+    /**
+     * @param query The user's question or information request regarding the application.
+     * @return A formatted response containing the most relevant documentation excerpts.
+     * 
+     * <p>
+     * This method is intended for integration with conversational AI systems (such as ChatGPT),
+     * enabling them to provide accurate and context-aware answers about the application's functionality.
+     * </p>
+     */
+    @Tool(description = "Retrieves functional information about the application based on the provided query.\r\n" + //
+                "     * It performs a semantic search over the application's documentation and returns the most relevant results.")
     public String getDocumentation(String query) {
+        logRequestDetails(query);
+        
+        String filterExpression = buildFilterExpression();
+        logger.info("[TOOL]LLM DocumentationTool Getting documentation for filterExpression: " + filterExpression);
 
+        SearchRequest request = buildSearchRequest(query, filterExpression);
+        List<Document> docs = this.vectorStore.similaritySearch(request);
+        
+        logger.info("Number of VDB retrieved documents: " + docs.size());
+        
+        return formatDocumentsResponse(docs);
+    }
+    
+    /**
+     * Registra i dettagli della richiesta nei log.
+     * 
+     * @param query La query di ricerca
+     */
+    private void logRequestDetails(String query) {
         logger.info("[TOOL]LLM DocumentationTool Getting documentation for query: " + query);
         logger.info("[TOOL]LLM DocumentationTool Getting documentation for project: " + this.project);
         logger.info("[TOOL]LLM DocumentationTool Getting documentation for vectorStore: " + this.vectorStore);
-        String filterExpression =  "'KsProjectName' == '"+ this.project +"' AND 'KsDoctype' == 'functional'";
+    }
-
+    
-        logger.info("[TOOL]LLM DocumentationTool Getting documentation for filterExpression: " + filterExpression);
+    /**
-
+     * Costruisce l'espressione di filtro per la ricerca.
-
+     * 
-        SearchRequest request = SearchRequest.builder()
+     * @return L'espressione di filtro formattata
-        .query(query)
+     */
-        .topK(3)
+    private String buildFilterExpression() {
-        .similarityThreshold(0.7)
+        return "'KsProjectName' == '"+ this.project +"' AND 'KsDoctype' == 'functional'";
-        .filterExpression( filterExpression).build();
+    }
-        
+    
-  
+    /**
-        List<Document> docs  = this.vectorStore.similaritySearch(request);
+     * Costruisce la richiesta di ricerca.
-        
+     * 
-        logger.info("Number of VDB retrieved documents: " + docs.size());
+     * @param query La query di ricerca
-
+     * @param filterExpression L'espressione di filtro
-        String docToolResponse = "";
+     * @return La richiesta di ricerca configurata
-        for (Document doc : docs) {
+     */
-            docToolResponse +=  "-------USE THIS AS PART OF YOUR CONTEXT----------------------------------------- \n";
+    private SearchRequest buildSearchRequest(String query, String filterExpression) {
-
+        return SearchRequest.builder()
-            docToolResponse += doc.getText() + "------------------------------------------------------------------------------------------ \n";
+            .query(query)
+            .topK(DEFAULT_TOP_K)
+            .similarityThreshold(DEFAULT_SIMILARITY_THRESHOLD)
+            .filterExpression(filterExpression)
+            .build();
+    }
+    
+    /**
+     * Formatta i documenti recuperati in una risposta leggibile.
+     * 
+     * @param docs Lista di documenti recuperati
+     * @return Risposta formattata contenente i testi dei documenti
+     */
+    private String formatDocumentsResponse(List<Document> docs) {
+        if (docs.isEmpty()) {
+            return "Nessun documento trovato per la query.";
         }
-
+        
-
+        StringBuilder response = new StringBuilder();
-		 
+        for (Document doc : docs) {
-
+            response.append("-------USE THIS AS PART OF YOUR CONTEXT-----------------------------------------\n")
-        return docToolResponse;
+                   .append(doc.getText())
+                   .append("------------------------------------------------------------------------------------------\n");
+        }
+        
+        return response.toString();
     }