Fix : TTS crash + perf improvement + router error fix

README.md

@@ -21,13 +21,14 @@
 ## Installation  
 
 ### 1️⃣ **Install Dependencies**  
-Make sure you have [Ollama](https://ollama.com/) installed, then run:  
 ```sh
 pip3 install -r requirements.txt
 ```
 
 ### 2️⃣ **Download Models**  
 
+Make sure you have [Ollama](https://ollama.com/) installed.
+
 Download the `deepseek-r1:7b` model from [DeepSeek](https://deepseek.com/models)
 
 ```sh

config.ini

@@ -1,9 +1,10 @@
 [MAIN]
-is_local = True
-provider_name = ollama
+is_local = False
+provider_name = server
 provider_model = deepseek-r1:14b
-provider_server_address = 127.0.0.1:11434
-agent_name = jarvis
+provider_server_address = 192.168.1.100:5000
+agent_name = Eva
 recover_last_session = True
+save_session = True
 speak = True
-listen = False
+listen = True

main.py

@@ -49,6 +49,8 @@ def main():
         interaction.get_user()
         interaction.think()
         interaction.show_answer()
+    if config.getboolean('MAIN', 'save_session'):
+        interaction.save_session()
 
 if __name__ == "__main__":
     main()

sources/interaction.py

@@ -39,6 +39,10 @@ class Interaction:
     def recover_last_session(self):
         for agent in self.agents:
             agent.memory.load_memory()
+    
+    def save_session(self):
+        for agent in self.agents:
+            agent.memory.save_memory()
 
     def is_active(self):
         return self.is_active
@@ -78,9 +82,11 @@ class Interaction:
         return query
     
     def think(self):
-        if self.last_query is None:
+        if self.last_query is None or len(self.last_query) == 0:
             return
         agent = self.router.select_agent(self.last_query)
+        if agent is None:
+            return
         if self.current_agent != agent:
             self.current_agent = agent
             # get history from previous agent

sources/memory.py

@@ -55,7 +55,9 @@ class Memory():
                 date = filename.split('_')[1]
                 saved_sessions.append((filename, date))
         saved_sessions.sort(key=lambda x: x[1], reverse=True)
-        return saved_sessions[0][0]
+        if len(saved_sessions) > 0:
+            return saved_sessions[0][0]
+        return None
 
     def load_memory(self) -> None:
         if not os.path.exists(self.conversation_folder):

sources/router.py

@@ -26,7 +26,7 @@ class AgentRouter:
         return result
     
     def select_agent(self, text: str) -> Agent:
-        if text is None:
+        if len(self.agents) == 0 or len(self.labels) == 0:
             return self.agents[0]
         result = self.classify_text(text)
         for agent in self.agents:

sources/speech_to_text.py

@@ -12,7 +12,7 @@ audio_queue = queue.Queue()
 done = False
 
 class AudioRecorder:
-    def __init__(self, format=pyaudio.paInt16, channels=1, rate=44100, chunk=8192, record_seconds=7, verbose=False):
+    def __init__(self, format=pyaudio.paInt16, channels=1, rate=4096, chunk=8192, record_seconds=7, verbose=False):
         self.format = format
         self.channels = channels
         self.rate = rate
@@ -60,8 +60,8 @@ class AudioRecorder:
 class Transcript:
     def __init__(self) -> None:
         self.last_read = None
-        device = "cuda:0" if torch.cuda.is_available() else "cpu"
-        torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+        device = self.get_device()
+        torch_dtype = torch.float16 if device == "cuda" else torch.float32
         model_id = "distil-whisper/distil-medium.en"
         
         model = AutoModelForSpeechSeq2Seq.from_pretrained(
@@ -75,11 +75,26 @@ class Transcript:
             model=model,
             tokenizer=processor.tokenizer,
             feature_extractor=processor.feature_extractor,
-            max_new_tokens=128,
+            max_new_tokens=24, # a human say around 20 token in 7s
             torch_dtype=torch_dtype,
             device=device,
         )
-
+    
+    def get_device(self):
+        if torch.backends.mps.is_available():
+            return "mps"
+        if torch.cuda.is_available():
+            return "cuda:0"
+        else:
+            return "cpu"
+    
+    def remove_hallucinations(self, text: str):
+        # TODO find a better way to do this
+        common_hallucinations = ['Okay.', 'Thank you.', 'Thank you for watching.', 'You\'re', 'Oh', 'you', 'Oh.', 'Uh', 'Oh,', 'Mh-hmm', 'Hmm.']
+        for hallucination in common_hallucinations:
+            text = text.replace(hallucination, "")
+        return text
+    
     def transcript_job(self, audio_data: np.ndarray, sample_rate: int = 16000):
         if audio_data.dtype != np.float32:
             audio_data = audio_data.astype(np.float32) / np.iinfo(audio_data.dtype).max
@@ -88,7 +103,7 @@ class Transcript:
         if sample_rate != 16000:
             audio_data = librosa.resample(audio_data, orig_sr=sample_rate, target_sr=16000)
         result = self.pipe(audio_data)
-        return result["text"]
+        return self.remove_hallucinations(result["text"])
 
 class AudioTranscriber:
     def __init__(self, ai_name: str, verbose=False):
@@ -103,16 +118,18 @@ class AudioTranscriber:
             'ES': [f"{self.ai_name}"]
         }
         self.confirmation_words = {
-            'EN': ["do it", "go ahead", "execute", "run", "start", "thanks", "would ya", "please", "okay?", "proceed", "continue", "go on", "do that", "do that thing"],
-            'FR': ["fais-le", "vas-y", "exécute", "lance", "commence", "merci", "tu veux bien", "s'il te plaît", "d'accord ?", "poursuis", "continue", "vas-y", "fais ça", "fais ce truc"],
-            'ZH': ["做吧", "继续", "执行", "运行", "开始", "谢谢", "可以吗", "请", "好吗", "进行", "继续", "往前走", "做那个", "做那件事"],
+            'EN': ["do it", "go ahead", "execute", "run", "start", "thanks", "would ya", "please", "okay?", "proceed", "continue", "go on", "do that", "go it", "do you understand?"],
+            'FR': ["fais-le", "vas-y", "exécute", "lance", "commence", "merci", "tu veux bien", "s'il te plaît", "d'accord ?", "poursuis", "continue", "vas-y", "fais ça", "compris"],
+            'ZH': ["做吧", "继续", "执行", "运行", "开始", "谢谢", "可以吗", "请", "好吗", "进行", "继续", "往前走", "做那个", "做那件事", "聽得懂"],
             'ES': ["hazlo", "adelante", "ejecuta", "corre", "empieza", "gracias", "lo harías", "por favor", "¿vale?", "procede", "continúa", "sigue", "haz eso", "haz esa cosa"]
         }
         self.recorded = ""
 
     def get_transcript(self):
+        global done
         buffer = self.recorded
         self.recorded = ""
+        done = False
         return buffer
 
     def _transcribe(self):