From 042248367dace26b45d88246795b8592653affef Mon Sep 17 00:00:00 2001
From: Florinda <dalia.florinda@accenture.com>
Date: Tue, 18 Feb 2025 14:55:47 +0100
Subject: [PATCH] update summarize 2

---
 .../stepSolvers/SummarizeDocSolver.java       | 76 ++++++++++++-------
 1 file changed, 50 insertions(+), 26 deletions(-)

diff --git a/src/main/java/com/olympus/hermione/stepSolvers/SummarizeDocSolver.java b/src/main/java/com/olympus/hermione/stepSolvers/SummarizeDocSolver.java
index 389978e..12c7b2e 100644
--- a/src/main/java/com/olympus/hermione/stepSolvers/SummarizeDocSolver.java
+++ b/src/main/java/com/olympus/hermione/stepSolvers/SummarizeDocSolver.java
@@ -44,6 +44,8 @@ public class SummarizeDocSolver extends StepSolver {
     private int percent_summarize;
     private Integer maxTokenChunk;
     private String qai_custom_memory_id;
+    private Integer max_output_token;
+    private String qai_system_prompt_template_minimum;
     // private boolean qai_load_graph_schema=false;
 
     Logger logger = (Logger) LoggerFactory.getLogger(SummarizeDocSolver.class);
@@ -67,6 +69,12 @@ public class SummarizeDocSolver extends StepSolver {
         this.percent_summarize = Integer.parseInt((String) this.step.getAttributes().get("percent_summarize"));
 
         this.qai_custom_memory_id = (String) this.step.getAttributes().get("qai_custom_memory_id");
+
+        this.max_output_token = Integer.parseInt((String) this.step.getAttributes().get("max_output_token"));
+
+        this.qai_system_prompt_template_minimum = attributeParser
+                .parse((String) this.step.getAttributes().get("qai_system_prompt_template_minimum"));
+
     }
 
     @Override
@@ -94,21 +102,29 @@ public class SummarizeDocSolver extends StepSolver {
             int charCount = text.length();
 
             // Stima media caratteri per token
-            double charPerToken = (double) charCount / tokenCount;
+            // double charPerToken = (double) charCount / tokenCount;
+
+            //Double output_char = (double) charCount * ((double) this.percent_summarize / 100.0);
+            Double min_output_token = (double) tokenCount * ((double) this.percent_summarize / 100.0);
+            String content = new String("");
+            content = this.qai_system_prompt_template.replace("max_number_token",
+                    max_output_token.toString());
+
+            if (min_output_token < max_output_token) {
+                content += this.qai_system_prompt_template_minimum.replace(
+                        "min_number_token",
+                        min_output_token.toString());
+            }
 
-            Double output_char = (double) charCount * ((double) this.percent_summarize / 100.0);
-            Integer output_char_int = output_char.intValue();
-            this.qai_system_prompt_template = this.qai_system_prompt_template.replace("number_char",
-                    output_char_int.toString());
             // **Fase di Summarization**
             String summarizedText = summarize(text); // 🔹 Applica la funzione di riassunto
             // String template = this.qai_system_prompt_template+" The output length should
             // be of " + output_char + " characters";
-            logger.info("template: " + this.qai_system_prompt_template);
+            logger.info("template: " + content);
             // Creazione dei messaggi per il modello AI
             Message userMessage = new UserMessage(summarizedText);
-            Message systemMessage = new SystemMessage(this.qai_system_prompt_template);
-
+            Message systemMessage = new SystemMessage(content);
+            logger.info("template: " + systemMessage.getContent().toString());
             CallResponseSpec resp = chatClient.prompt()
                     .messages(userMessage, systemMessage)
                     .advisors(advisor -> advisor
@@ -192,26 +208,34 @@ public class SummarizeDocSolver extends StepSolver {
 
     // Metodo di riassunto per singolo chunk
     private String summarizeChunk(String chunk) {
-        try {
-            this.qai_system_prompt_template_chunk = this.qai_system_prompt_template_chunk.replace("number_char",
-                    maxTokenChunk.toString());
+        String content = new String("");
 
-            Message chunkMessage = new UserMessage(chunk);
-            Message systemMessage = new SystemMessage(qai_system_prompt_template_chunk);
-
-            CallResponseSpec resp = chatClient.prompt()
-                    .messages(chunkMessage, systemMessage)
-                   /* .advisors(advisor -> advisor
-                            .param("chat_memory_conversation_id",
-                                    this.scenarioExecution.getId() + this.qai_custom_memory_id)
-                            .param("chat_memory_response_size", 100))*/
-                    .call();
-
-            return resp.content();
-        } catch (Exception e) {
-            e.printStackTrace();
-            return chunk.substring(0, Math.max(1, chunk.length() / 10)); // Fallback
+        if (maxTokenChunk < max_output_token) {
+            content = this.qai_system_prompt_template_chunk.replace("max_number_token",
+            maxTokenChunk.toString());
+        }else{
+            content = this.qai_system_prompt_template_chunk.replace("max_number_token",
+            max_output_token.toString());
         }
+
+        Message chunkMessage = new UserMessage(chunk);
+        Message systemMessage = new SystemMessage(
+            content);
+
+        logger.info("template chunk: " + content);
+
+        CallResponseSpec resp = chatClient.prompt()
+                .messages(chunkMessage, systemMessage)
+                /*
+                 * .advisors(advisor -> advisor
+                 * .param("chat_memory_conversation_id",
+                 * this.scenarioExecution.getId() + this.qai_custom_memory_id)
+                 * .param("chat_memory_response_size", 100))
+                 */
+                .call();
+
+        return resp.content();
+
     }
 
 }