sessions/next24/books-genai-vertex-langchain4j/src/main/java/services/web/BookAnalysisController.java [70:91]:
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  public ResponseEntity<String> bookAnalysis(@RequestBody BookRequest bookRequest, @RequestParam(name = "contentCharactersLimit", defaultValue = "6000") Integer contentCharactersLimit){

    long start = System.currentTimeMillis();
    logger.info("Book analysis flow : start");

    // Prompt AlloyDB for the embeddings for the book in the request
    List<Map<String, Object>> responseBook = booksService.prompt(bookRequest, contentCharactersLimit);
    logger.info("Book analysis flow: retrieve embeddings from AlloyDB AI: " + (System.currentTimeMillis() - start) + "ms");

    // build prompt to query LLM with the augmented context
    String promptWithContext = PromptUtility.formatPromptBookAnalysis(bookRequest, responseBook, bookRequest.keyWords());

    logger.info("Book analysis flow - Model: " + model);
    start = System.currentTimeMillis();

    // submit prompt to the LLM via LLM orchestration framework
    String response = vertexAIClient.promptModel(promptWithContext);
    logger.info("Book analysis flow: prompt LLM: " + (System.currentTimeMillis() - start) + "ms");

    // return the response to the caller
    return new ResponseEntity<>(response, HttpStatus.OK);
  }
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sessions/fall24/books-genai-vertex-langchain4j/src/main/java/services/web/BookAnalysisController.java [70:91]:
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  public ResponseEntity<String> bookAnalysis(@RequestBody BookRequest bookRequest, @RequestParam(name = "contentCharactersLimit", defaultValue = "6000") Integer contentCharactersLimit){

    long start = System.currentTimeMillis();
    logger.info("Book analysis flow : start");

    // Prompt AlloyDB for the embeddings for the book in the request
    List<Map<String, Object>> responseBook = booksService.prompt(bookRequest, contentCharactersLimit);
    logger.info("Book analysis flow: retrieve embeddings from AlloyDB AI: " + (System.currentTimeMillis() - start) + "ms");

    // build prompt to query LLM with the augmented context
    String promptWithContext = PromptUtility.formatPromptBookAnalysis(bookRequest, responseBook, bookRequest.keyWords());

    logger.info("Book analysis flow - Model: " + model);
    start = System.currentTimeMillis();

    // submit prompt to the LLM via LLM orchestration framework
    String response = vertexAIClient.promptModel(promptWithContext);
    logger.info("Book analysis flow: prompt LLM: " + (System.currentTimeMillis() - start) + "ms");

    // return the response to the caller
    return new ResponseEntity<>(response, HttpStatus.OK);
  }
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