fix unit tests

tests/test_rnnoise_cancellation.py

@@ -1,23 +1,25 @@
 import asyncio
-import os
+import unittest
-import wave
 
 import numpy as np
 import pytest
 
+try:
+    import pyrnnoise
+except ImportError:
+    pyrnnoise = None
+
 from pipecat.audio.filters.rnnoise_filter import RNNoiseFilter
 from pipecat.frames.frames import FilterEnableFrame
 
 
-async def test_rnnoise_cancellation_functionality():
+class TestRNNoiseCancellation(unittest.IsolatedAsyncioTestCase):
+    async def test_rnnoise_cancellation_functionality(self):
         print("\nStarting Noise Cancellation Test")
 
         # 1. Check for pyrnnoise
-    try:
+        if pyrnnoise is None:
-        import pyrnnoise
+            self.skipTest("pyrnnoise not installed. Cannot verify actual noise cancellation.")
-    except ImportError:
-        pytest.skip("pyrnnoise not installed. Cannot verify actual noise cancellation.")
-        return
 
         # 2. Generate clean speech-like audio (Harmonic series)
         sample_rate = 48000
@@ -140,7 +142,9 @@ async def test_rnnoise_cancellation_functionality():
             noise_power_output = np.mean(aligned_output[silent_mask].astype(float) ** 2)
             print(f"Noise Power in Silence (Input): {noise_power_input:.2f}")
             print(f"Noise Power in Silence (Output): {noise_power_output:.2f}")
-        assert noise_power_output < noise_power_input, "Noise power in silence not reduced"
+            self.assertLess(
+                noise_power_output, noise_power_input, "Noise power in silence not reduced"
+            )
         else:
             print("Warning: Not enough silent samples found for noise floor check.")
 
@@ -154,14 +158,12 @@ async def test_rnnoise_cancellation_functionality():
                 "Warning: Overall MSE did not improve (speech distortion?). Relying on Noise Power check."
             )
             # If we passed the noise power check above, we are good.
-        assert np.sum(silent_mask) > 1000 and np.mean(
+            self.assertTrue(
-            aligned_output[silent_mask].astype(float) ** 2
+                np.sum(silent_mask) > 1000
-        ) < np.mean(aligned_noisy[silent_mask].astype(float) ** 2)
+                and np.mean(aligned_output[silent_mask].astype(float) ** 2)
+                < np.mean(aligned_noisy[silent_mask].astype(float) ** 2)
+            )
         else:
-        assert mse_output < mse_input, "MSE did not improve"
+            self.assertLess(mse_output, mse_input, "MSE did not improve")
 
         print("Test Passed: Noise cancellation verified.")
-
-
-if __name__ == "__main__":
-    asyncio.run(test_rnnoise_cancellation_functionality())

tests/test_rnnoise_filter.py

@@ -8,11 +8,20 @@ import unittest
 
 import numpy as np
 
+try:
+    import pyrnnoise
+except ImportError:
+    pyrnnoise = None
+
 from pipecat.audio.filters.rnnoise_filter import RNNoiseFilter
 from pipecat.frames.frames import FilterEnableFrame
 
 
 class TestRNNoiseFilter(unittest.IsolatedAsyncioTestCase):
+    def setUp(self):
+        if pyrnnoise is None:
+            self.skipTest("pyrnnoise not installed")
+
     async def test_rnnoise_filter_reduces_noise(self):
         """Test that RNNoise filter reduces noise in audio."""
         filter = RNNoiseFilter()

tests/test_rnnoise_resampling.py

@@ -1,26 +1,24 @@
 import asyncio
 import sys
-from unittest.mock import MagicMock
+import unittest
+from unittest.mock import MagicMock, patch
 
 import numpy as np
-import pytest
 
-# Mock pyrnnoise BEFORE importing RNNoiseFilter
+# We don't need to mock sys.modules here if we use patch on the imported module member
-mock_pyrnnoise = MagicMock()
+# But we need to ensure RNNoiseFilter is imported so we can patch its member
-mock_rnnoise_class = MagicMock()
-mock_pyrnnoise.RNNoise = mock_rnnoise_class
-sys.modules["pyrnnoise"] = mock_pyrnnoise
-
-# Now import the filter
 try:
     from pipecat.audio.filters.rnnoise_filter import RNNoiseFilter
     from pipecat.frames.frames import FilterEnableFrame
 except ImportError as e:
+    # If dependencies are missing (like numpy?), we can't test
     print(f"Failed to import RNNoiseFilter: {e}")
     sys.exit(1)
 
 
-async def test_rnnoise_resampling_16k_to_48k_and_back():
+class TestRNNoiseResampling(unittest.IsolatedAsyncioTestCase):
+    @patch("pipecat.audio.filters.rnnoise_filter.RNNoise")
+    async def test_rnnoise_resampling_16k_to_48k_and_back(self, mock_rnnoise_class):
         print("\nStarting Resampling Test: 16kHz -> 48kHz -> 16kHz")
 
         # Configure Mock with buffering behavior
@@ -56,9 +54,12 @@ async def test_rnnoise_resampling_16k_to_48k_and_back():
         audio_data = (np.sin(2 * np.pi * 440 * t) * 32767).astype(np.int16)
         audio_bytes = audio_data.tobytes()
 
-    print(f"Input audio: {len(audio_bytes)} bytes, {len(audio_data)} samples at {sample_rate}Hz")
+        print(
+            f"Input audio: {len(audio_bytes)} bytes, {len(audio_data)} samples at {sample_rate}Hz"
+        )
 
         # 2. Initialize RNNoiseFilter
+        # This will use the patched RNNoise
         rnnoise_filter = RNNoiseFilter()
         await rnnoise_filter.start(sample_rate)
 
@@ -81,38 +82,32 @@ async def test_rnnoise_resampling_16k_to_48k_and_back():
 
         # 4. Verify output length
         # Expect roughly same length
-    # Input: 16000 samples.
-    # Upsampled to 48000.
-    # 48000 / 480 = 100 chunks.
-    # So we expect roughly 100 calls to process_chunk.
         expected_chunks = (len(audio_data) * 48000 // sample_rate) // 480
         print(f"Expected chunks: ~{expected_chunks}")
 
         # Check that we actually processed something
-    assert processed_chunks_count >= expected_chunks - 5, "Too few chunks processed"
+        self.assertGreaterEqual(
+            processed_chunks_count, expected_chunks - 5, "Too few chunks processed"
+        )
 
         # Check output length
-    assert len(processed_audio) > 0, "Output should not be empty"
+        self.assertGreater(len(processed_audio), 0, "Output should not be empty")
 
         # Check length matches input (with some tolerance for buffering latency)
-    # Since we don't flush the filter explicitly (no flush method in RNNoiseFilter yet),
-    # some data might remain in buffers.
-    # Max loss:
-    # - Resampler input buffer
-    # - RNNoise buffer (max 480 samples = 10ms)
-    # - Resampler output buffer
-
         # 100ms tolerance?
         byte_tolerance = int(0.2 * sample_rate * 2)
-    assert len(processed_audio) >= len(audio_bytes) - byte_tolerance, (
+        self.assertGreaterEqual(
-        f"Output too short: {len(processed_audio)} vs {len(audio_bytes)}"
+            len(processed_audio),
+            len(audio_bytes) - byte_tolerance,
+            f"Output too short: {len(processed_audio)} vs {len(audio_bytes)}",
         )
-    assert len(processed_audio) <= len(audio_bytes) + byte_tolerance, (
+        self.assertLessEqual(
-        f"Output too long: {len(processed_audio)} vs {len(audio_bytes)}"
+            len(processed_audio),
+            len(audio_bytes) + byte_tolerance,
+            f"Output too long: {len(processed_audio)} vs {len(audio_bytes)}",
         )
 
         # 5. Check sample rate / pitch preservation
-    # If we upsampled and downsampled correctly, the pitch should be 440Hz.
         output_data = np.frombuffer(processed_audio, dtype=np.int16)
 
         if len(output_data) > 2000:
@@ -127,10 +122,8 @@ async def test_rnnoise_resampling_16k_to_48k_and_back():
             peak_freq = freqs[peak_idx]
 
             print(f"Peak frequency: {peak_freq:.2f} Hz")
-        assert abs(peak_freq - 440) < 50, f"Frequency shifted significantly: {peak_freq} vs 440"
+            self.assertLess(
+                abs(peak_freq - 440), 50, f"Frequency shifted significantly: {peak_freq} vs 440"
+            )
 
         print("Test Passed: Resampling logic verified (with mocked RNNoise).")
-
-
-if __name__ == "__main__":
-    asyncio.run(test_rnnoise_resampling_16k_to_48k_and_back())