fix(chatterbox): chunk long text (#6407)

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

backend/python/chatterbox/backend.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 """
-This is an extra gRPC server of LocalAI for Bark TTS
+This is an extra gRPC server of LocalAI for Chatterbox TTS
 """
 from concurrent import futures
 import time
@@ -16,6 +16,7 @@ import torchaudio as ta
 from chatterbox.tts import ChatterboxTTS
 from chatterbox.mtl_tts import ChatterboxMultilingualTTS
 import grpc
+import tempfile
 
 def is_float(s):
     """Check if a string can be converted to float."""
@@ -32,11 +33,79 @@ def is_int(s):
     except ValueError:
         return False
 
+def split_text_at_word_boundary(text, max_length=250):
+    """
+    Split text at word boundaries without truncating words.
+    Returns a list of text chunks.
+    """
+    if not text or len(text) <= max_length:
+        return [text]
+    
+    chunks = []
+    words = text.split()
+    current_chunk = ""
+    
+    for word in words:
+        # Check if adding this word would exceed the limit
+        if len(current_chunk) + len(word) + 1 <= max_length:
+            if current_chunk:
+                current_chunk += " " + word
+            else:
+                current_chunk = word
+        else:
+            # If current chunk is not empty, add it to chunks
+            if current_chunk:
+                chunks.append(current_chunk)
+                current_chunk = word
+            else:
+                # If a single word is longer than max_length, we have to include it anyway
+                chunks.append(word)
+                current_chunk = ""
+    
+    # Add the last chunk if it's not empty
+    if current_chunk:
+        chunks.append(current_chunk)
+    
+    return chunks
+
+def merge_audio_files(audio_files, output_path, sample_rate):
+    """
+    Merge multiple audio files into a single audio file.
+    """
+    if not audio_files:
+        return
+    
+    if len(audio_files) == 1:
+        # If only one file, just copy it
+        import shutil
+        shutil.copy2(audio_files[0], output_path)
+        return
+    
+    # Load all audio files
+    waveforms = []
+    for audio_file in audio_files:
+        waveform, sr = ta.load(audio_file)
+        if sr != sample_rate:
+            # Resample if necessary
+            resampler = ta.transforms.Resample(sr, sample_rate)
+            waveform = resampler(waveform)
+        waveforms.append(waveform)
+    
+    # Concatenate all waveforms
+    merged_waveform = torch.cat(waveforms, dim=1)
+    
+    # Save the merged audio
+    ta.save(output_path, merged_waveform, sample_rate)
+    
+    # Clean up temporary files
+    for audio_file in audio_files:
+        if os.path.exists(audio_file):
+            os.remove(audio_file)
+
 _ONE_DAY_IN_SECONDS = 60 * 60 * 24
 
 # If MAX_WORKERS are specified in the environment use it, otherwise default to 1
 MAX_WORKERS = int(os.environ.get('PYTHON_GRPC_MAX_WORKERS', '1'))
-COQUI_LANGUAGE = os.environ.get('COQUI_LANGUAGE', None)
 
 # Implement the BackendServicer class with the service methods
 class BackendServicer(backend_pb2_grpc.BackendServicer):
@@ -118,10 +187,33 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             # add options to kwargs
             kwargs.update(self.options)
 
-            # Generate audio using ChatterboxTTS
-            wav = self.model.generate(request.text, **kwargs)
-            # Save the generated audio
-            ta.save(request.dst, wav, self.model.sr)
+            # Check if text exceeds 250 characters
+            # (chatterbox does not support long text)
+            # https://github.com/resemble-ai/chatterbox/issues/60
+            # https://github.com/resemble-ai/chatterbox/issues/110
+            if len(request.text) > 250:
+                # Split text at word boundaries
+                text_chunks = split_text_at_word_boundary(request.text, max_length=250)
+                print(f"Splitting text into chunks of 250 characters: {len(text_chunks)}", file=sys.stderr)
+                # Generate audio for each chunk
+                temp_audio_files = []
+                for i, chunk in enumerate(text_chunks):
+                    # Generate audio for this chunk
+                    wav = self.model.generate(chunk, **kwargs)
+                    
+                    # Create temporary file for this chunk
+                    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
+                    temp_file.close()
+                    ta.save(temp_file.name, wav, self.model.sr)
+                    temp_audio_files.append(temp_file.name)
+                
+                # Merge all audio files
+                merge_audio_files(temp_audio_files, request.dst, self.model.sr)
+            else:
+                # Generate audio using ChatterboxTTS for short text
+                wav = self.model.generate(request.text, **kwargs)
+                # Save the generated audio
+                ta.save(request.dst, wav, self.model.sr)
             
         except Exception as err:
             return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")