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update summarize 2

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This commit is contained in:
Florinda
2025-02-18 14:55:47 +01:00
parent d5d3fb9e1b
commit 042248367d
1 changed files with 50 additions and 26 deletions
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76
src/main/java/com/olympus/hermione/stepSolvers/SummarizeDocSolver.java
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@@ -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();
}
}