added readme_util

kafka_utils/document_translator.py

 from kafka_utils.producer import get_producer
 from kafka_utils.consumer import get_consumer
 import json
-import anuvada
 import tools.sp_enc_dec as sp
 import ancillary_functions_anuvaad.ancillary_functions as ancillary_functions
 import ancillary_functions_anuvaad.sc_preface_handler as sc_preface_handler
@@ -65,46 +64,3 @@ def doc_translator(translation_server,c_topic,p_topic):
         logger.error("Unexpected error: %s"% sys.exc_info()[0])
         logger.error("error in doc_translator: {}".format(e))
         doc_translator(translation_server,c_topic,p_topic)
-
-# def nmt_translation(translation_server,c,p,producer_topic):
-#     iq =0
-#     out = {}
-#     msg_count = 0
-#     msg_sent = 0
-#     try:
-#         for msg in c:
-#             msg_count +=1
-#             logger.info("*******************msg receive count*********:{}".format(msg_count))
-#             iq = iq +1
-#             inputs = (msg.value)
-#             logger.info(inputs)
-
-#             if inputs is not None and len(inputs) is not 0:
-#                 if inputs['url_end_point'] == 'translation_en':
-#                     logger.info("Running kafka on  {}".format(inputs['url_end_point']))
-#                     logger.info("Running kafka-translation on  {}".format(inputs['message']))
-#                     out = translate_util.from_en(inputs['message'], translation_server)
-#                 elif inputs['url_end_point'] == 'translation_hi':
-#                     logger.info("Running kafka on  {}".format(inputs['url_end_point']))
-#                     logger.info("Running kafka-translation on  {}".format(inputs['message']))
-#                     out = translate_util.from_hindi(inputs['message'], translation_server)
-#                     logger.info("final output kafka-translation_hi:{}".format(out))  
-#                 elif inputs['url_end_point'] == "translate-anuvaad":
-#                     logger.info("Running kafka on  {}".format(inputs['url_end_point']))
-#                     logger.info("Running kafka-translation on  {}".format(inputs['message']))  
-#                     out = translate_util.translate_func(inputs['message'], translation_server)
-#                     logger.info("final output kafka-translate-anuvaad:{}".format(out)) 
-#                 else:
-#                     logger.info("Incorrect url_end_point for KAFKA")
-#                     out['status'] = statusCode["KAFKA_INVALID_REQUEST"]
-#                     out['response_body'] = []
-
-                
-#             p.send(producer_topic, value={'out':out})
-#             p.flush()
-#             msg_sent += 1
-#             logger.info("*******************msg sent count*********:{}".format(msg_sent))
-#     except Exception  as e:
-#         logger.error("Error in kafka_document_translator:nmt_translation: %s"% sys.exc_info()[0])
-#         logger.error("Error in kafka_document_translator:nmt_translation: {}".format(e))  
-#         raise  
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translation_util/README_UTILS.md

+Interactive Translation
+
+Steps involved:
+1. Convert the trained model .pt file into binary file along with source and target vocabulary
+   The "interactive-model-convert" api expects following input:
+   1. inp_model_path - path of model(.pt) file which needs to be converted
+   2. out_dir - output path where binary model file and vocabulary are saved
+
+2. The converted model has to be updated in available_models/interactive_models/iconf.json file along with model id and the path where it
+   is saved(i.e out_dir)
+
+3. Make corresponding model changes in interactive_translation function and deploy
+4. The interactive apis can be accessed by running interactive_server.py   
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