fix compilation and build issues

virtual-assistant-rasa/config.py

@@ -19,12 +19,12 @@
 }
 
 rasa_config = {
-    "VERBOSE": False, # Print logs/details for diagnostics
+    "VERBOSE": True, # Print logs/details for diagnostics
     "RASA_API_URL": "http://localhost:5005", # Replace the IP & Port with the rasa-weatherbot's IP & Port
 }
 
 asr_config = {
-    "VERBOSE": False, # Print logs/details for diagnostics
+    "VERBOSE": True, # Print logs/details for diagnostics
     "SAMPLING_RATE": 16000, # The Sampling Rate for the audio input file. The only value currently supported is 16000
     "LANGUAGE_CODE": "en-US", # The language code as a BCP-47 language tag. The only value currently supported is "en-US"
     "ENABLE_AUTOMATIC_PUNCTUATION": True, # Enable or Disable punctuation in the transcript generated. The only value currently supported by the chatbot is True (Although Riva ASR supports both True & False)

virtual-assistant-rasa/rasa-riva-weatherbot-webapp/client/webapplication/server/server.py

@@ -19,7 +19,7 @@
 from engineio.payload import Payload
 
 from config import client_config
-from riva.chatbot.chatbots_multiconversations_management import create_chatbot, get_new_user_conversation_index, get_chatbot
+from riva_local.chatbot.chatbots_multiconversations_management import create_chatbot, get_new_user_conversation_index, get_chatbot
 
 ''' Flask Initialization 
 '''

virtual-assistant-rasa/rasa-riva-weatherbot-webapp/main.py

@@ -9,7 +9,7 @@
 
 root_folder = (os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)))
 sys.path.append(root_folder)
-
+# print(root_folder)
 from config import client_config
 
 if __name__ == '__main__':

virtual-assistant-rasa/rasa-riva-weatherbot-webapp/riva_local/chatbot/chatbot.py

@@ -9,8 +9,8 @@
 
 from riva_local.asr.asr import ASRPipe
 from riva_local.rasa.rasa import RASAPipe
-from riva_local.tts.tts import TTSPipe
-# from riva_local.tts.tts_stream import TTSPipe
+# from riva_local.tts.tts import TTSPipe
+from riva_local.tts.tts_stream import TTSPipe
 
 class ChatBot(object):
     """ Class Implementing all the features of the chatbot"""

virtual-assistant-rasa/rasa-riva-weatherbot-webapp/riva_local/tts/tts.py

@@ -27,7 +27,7 @@ def __init__(self):
         self.sample_rate = tts_config["SAMPLE_RATE"] if "SAMPLE_RATE" in tts_config else SAMPLE_RATE
         self.language_code = tts_config["LANGUAGE_CODE"] if "LANGUAGE_CODE" in tts_config else LANGUAGE_CODE
         self.voice_name = tts_config["VOICE_NAME"] if "VOICE_NAME" in tts_config else VOICE_NAME
-        self.audio_encoding = ra.AudioEncoding.LINEAR_PCM
+        self.audio_encoding = riva.client.AudioEncoding.LINEAR_PCM
         self._buff = queue.Queue()
         self.closed = False
         self._flusher = bytes(np.zeros(dtype=np.int16, shape=(self.sample_rate, 1)))  # Silence audio

virtual-assistant-rasa/rasa-riva-weatherbot-webapp/riva_local/tts/tts_stream.py

@@ -22,7 +22,7 @@
 class TTSPipe(object):
     """Opens a gRPC channel to Riva TTS to synthesize speech
     from text in streaming mode."""
-
+    print('TTS started')
     def __init__(self):
         self.verbose = tts_config["VERBOSE"] if "VERBOSE" in tts_config else VERBOSE
         self.sample_rate = tts_config["SAMPLE_RATE"] if "SAMPLE_RATE" in tts_config else SAMPLE_RATE
@@ -48,6 +48,7 @@ def get_current_tts_duration(self):
 
     def fill_buffer(self, in_data):
         """To collect text responses from the state machine output, into a buffer."""
+        # print()
         if len(in_data):
             self._buff.put(in_data)
 

virtual-assistant-rasa/rasa-weatherbot/components.py

@@ -21,7 +21,7 @@
                                                  os.path.pardir)))
 sys.path.append(root_folder)
 
-from riva.nlp.nlp import get_intent_and_entities
+from riva_local.nlp.nlp import get_intent_and_entities
 
 
 class RivaNLPComponent(Component):
@@ -83,6 +83,7 @@ def __convert_to_rasa_intent(self, response):
         return intent
 
     def __convert_to_rasa_entities(self, response):
+        print(response)
         """Convert model output into the Rasa NLU compatible output format."""
         for entity in response["entities"]:
             entity["extractor"] = "RivaNLPExtractor"

virtual-assistant-rasa/rasa-weatherbot/riva_local/nlp/nlp.py

@@ -18,7 +18,7 @@
 import json
 
 auth = riva.client.Auth(uri=riva_config["RIVA_SPEECH_API_URL"])
-riva_nlp = riva.client.NLPService(auth)
+riva_nlp  = riva.client.NLPService(auth)
 
 # The default intent object for specifying the city
 SPECIFY_CITY_INTENT = { 'value': "specify_city", 'confidence': 1 }
@@ -31,8 +31,9 @@
 verbose = rivanlp_config["VERBOSE"] if "VERBOSE" in rivanlp_config else VERBOSE
 nlu_fallback_threshold = rivanlp_config["NLU_FALLBACK_THRESHOLD"] if "NLU_FALLBACK_THRESHOLD" in rivanlp_config else NLU_FALLBACK_THRESHOLD
 
-
+#  {}
 def get_intent_old(resp, result):
+    # result['intent'] = []
     if hasattr(resp, 'intent') and (hasattr(resp, 'domain') and resp.domain.class_name != "nomatch.none"):
         result['intent'] = { 'value': resp.intent.class_name, 'confidence': resp.intent.score }
         parentclassintent_index = result['intent']['value'].find(".")
@@ -51,6 +52,7 @@ def get_entities(resp, result):
     location_found_flag = False
     all_entities_class = {}
     all_entities = []
+    result['entities'] = []
     if hasattr(resp, 'slots'):
         for i in range(len(resp.slots)):
             slot_class = resp.slots[i].label[0].class_name.replace("\r", "")
@@ -110,8 +112,8 @@ def get_riva_output(text):
         print("[Riva NLU] Error during NLU request")
         return {'riva_error': 'riva_error'}
     entities = {}
-    get_intent(resp, entities)
-    get_slots(resp, entities)
+    get_intent_old(resp, entities)
+    get_entities(resp, entities)
     if 'location' not in entities:
         if verbose:
             print(f"[Riva NLU] Did not find any location in the string: {text}\n"