From e981d2d8fc2b60aad87c5e0c6cb299448dee4b80 Mon Sep 17 00:00:00 2001
From: "Hua.T" <126794161+HuaTNA@users.noreply.github.com>
Date: Sun, 11 Oct 2026 17:23:05 -0400
Subject: [PATCH] Forward backend options during streaming speech generation
 (#1389) (#1390)

---
 .../txtai/pipeline/audio/texttospeech.py      |  9 ++++---
 .../testaudio/testtexttospeech.py             | 27 ++++++++++++++++++-
 2 files changed, 31 insertions(+), 5 deletions(-)

diff --git a/src/python/txtai/pipeline/audio/texttospeech.py b/src/python/txtai/pipeline/audio/texttospeech.py
index eaf62db8..d48d9e08 100644
--- a/src/python/txtai/pipeline/audio/texttospeech.py
+++ b/src/python/txtai/pipeline/audio/texttospeech.py
@@ -92,7 +92,7 @@ class TextToSpeech(Pipeline):
 
         # Streaming response
         if stream:
-            return self.stream(texts, speaker, encoding)
+            return self.stream(texts, speaker, encoding, **kwargs)
 
         # Transform text to speech
         results = [self.execute(x, speaker, encoding, **kwargs) for x in texts]
@@ -137,7 +137,7 @@ class TextToSpeech(Pipeline):
 
         return exists
 
-    def stream(self, texts, speaker, encoding):
+    def stream(self, texts, speaker, encoding, **kwargs):
         """
         Iterates over texts, splits into segments and yields snippets of audio.
         This method is designed to integrate with streaming LLM generation.
@@ -146,6 +146,7 @@ class TextToSpeech(Pipeline):
             texts: list of input texts
             speaker: speaker id
             encoding: audio encoding format
+            kwargs: additional keyword args
 
         Returns:
             snippets of audio as NumPy arrays or audio bytes depending on encoding parameter
@@ -157,11 +158,11 @@ class TextToSpeech(Pipeline):
 
             if x == "\n" or (x.strip().endswith(".") and len([y for y in buffer if y]) > 2):
                 data, buffer = "".join(buffer), []
-                yield self.execute(data, speaker, encoding)
+                yield self.execute(data, speaker, encoding, **kwargs)
 
         if buffer:
             data = "".join(buffer)
-            yield self.execute(data, speaker, encoding)
+            yield self.execute(data, speaker, encoding, **kwargs)
 
     def execute(self, text, speaker, encoding, **kwargs):
         """
diff --git a/test/python/testpipeline/testaudio/testtexttospeech.py b/test/python/testpipeline/testaudio/testtexttospeech.py
index 09f6d70b..548d07e5 100644
--- a/test/python/testpipeline/testaudio/testtexttospeech.py
+++ b/test/python/testpipeline/testaudio/testtexttospeech.py
@@ -4,7 +4,9 @@ TextToSpeech module tests
 
 import unittest
 
-from unittest.mock import patch
+from unittest.mock import call, patch
+
+import numpy as np
 
 from txtai.pipeline import TextToSpeech
 
@@ -80,3 +82,26 @@ class TestTextToSpeech(unittest.TestCase):
         # Check that data is generated
         self.assertGreater(len(speech), 0)
         self.assertEqual(rate, 22050)
+
+    @patch("txtai.pipeline.audio.texttospeech.Kokoro")
+    @patch.object(TextToSpeech, "hasfile")
+    def testStreamingOptions(self, hasfile, kokoro):
+        """
+        Test backend options reach both flushed and final streaming segments
+        """
+
+        hasfile.side_effect = lambda _, name: name in ("model.onnx", "voices.json")
+        audio = np.array([0.1, -0.1], dtype=np.float32)
+        kokoro.return_value.return_value = (audio, 24000)
+        tts = TextToSpeech("neuml/kokoro-int8-onnx", rate=None)
+
+        chunks = list(tts(iter(["One ", "two ", "three.", "Tail"]), stream=True, speaker="af", speed=1.5, transcribe=False))
+
+        self.assertEqual(
+            kokoro.return_value.call_args_list,
+            [call("One two three.", "af", speed=1.5, transcribe=False), call("Tail", "af", speed=1.5, transcribe=False)],
+        )
+        self.assertEqual(len(chunks), 2)
+        for data, rate in chunks:
+            np.testing.assert_array_equal(data, audio)
+            self.assertEqual(rate, 24000)