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| import logging | |
| import io | |
| import base64 | |
| import matplotlib.pyplot as plt | |
| from ..text_analysis.semantic_analysis import perform_semantic_analysis | |
| from .flexible_analysis_handler import FlexibleAnalysisHandler | |
| logger = logging.getLogger(__name__) | |
| def encode_image_to_base64(image_data): | |
| if isinstance(image_data, str): # Si es una ruta de archivo | |
| with open(image_data, "rb") as image_file: | |
| encoded_string = base64.b64encode(image_file.read()).decode("utf-8") | |
| elif isinstance(image_data, bytes): # Si son datos de imagen en memoria | |
| encoded_string = base64.b64encode(image_data).decode("utf-8") | |
| else: | |
| raise ValueError("Invalid image data type. Expected string (file path) or bytes.") | |
| return encoded_string # | |
| def process_semantic_analysis(file_contents, nlp_model, lang_code): | |
| logger.info(f"Starting semantic analysis processing for language: {lang_code}") | |
| try: | |
| result = perform_semantic_analysis(file_contents, nlp_model, lang_code) | |
| #handler = FlexibleAnalysisHandler(result) | |
| #concept_graph = handler.get_graph('concept_graph') | |
| #entity_graph = handler.get_graph('entity_graph') | |
| #key_concepts = handler.get_key_concepts() | |
| concept_graph = result['concept_graph'] | |
| entity_graph = result['entity_graph'] | |
| key_concepts = result['key_concepts'] | |
| # Convertir los gráficos a base64 | |
| concept_graph_base64 = fig_to_base64(concept_graph) if concept_graph else None | |
| entity_graph_base64 = fig_to_base64(entity_graph) if entity_graph else None | |
| logger.info("Semantic analysis processing completed successfully") | |
| return concept_graph_base64, entity_graph_base64, key_concepts | |
| except Exception as e: | |
| logger.error(f"Error in semantic analysis processing: {str(e)}") | |
| return None, None, [] # Retorna valores vacíos en caso de error | |
| ''' | |
| logger = logging.getLogger(__name__) | |
| logging.basicConfig(level=logging.DEBUG) | |
| def process_semantic_analysis(file_contents, nlp_model, lang_code): | |
| logger.info(f"Starting semantic analysis for language: {lang_code}") | |
| try: | |
| logger.debug("Calling perform_semantic_analysis") | |
| result = perform_semantic_analysis(file_contents, nlp_model, lang_code) | |
| logger.debug(f"Result keys: {result.keys()}") | |
| logger.debug(f"Type of concept_graph: {type(result['concept_graph'])}") | |
| logger.debug(f"Type of entity_graph: {type(result['entity_graph'])}") | |
| logger.debug(f"Number of key_concepts: {len(result['key_concepts'])}") | |
| logger.info("Semantic analysis completed successfully") | |
| return result['concept_graph'], result['entity_graph'], result['key_concepts'] | |
| except Exception as e: | |
| logger.error(f"Error in semantic analysis: {str(e)}") | |
| raise | |
| ''' |