Apply ruff formatting fixes

test_assemblyai_custom.py

@@ -48,11 +48,11 @@ async def main():
     logger.remove(0)
     logger.add(sys.stderr, level=LOG_LEVEL)
 
-    logger.info("="*80)
+    logger.info("=" * 80)
     logger.info("AssemblyAI u3-rt-pro Custom Test")
-    logger.info("="*80)
+    logger.info("=" * 80)
     logger.info("Starting bot... Speak after you hear the greeting!")
-    logger.info("="*80)
+    logger.info("=" * 80)
 
     # Create local audio transport
     transport = LocalAudioTransport(
@@ -74,78 +74,63 @@ async def main():
         speech_model="u3-rt-pro",
         # speech_model="universal-streaming-english",
         # speech_model="universal-streaming-multilingual",
-
         # ====================================================================
         # Turn Detection Timing
         # ====================================================================
-
         # Minimum silence when confident about end of turn (milliseconds)
         # Default: 100ms | Higher = more patient | Lower = faster responses
         # Only used in Pipecat mode (vad_force_turn_endpoint=True)
         min_turn_silence=100000,
         # min_turn_silence=200,
         # min_turn_silence=300,
-
         # Maximum turn silence (milliseconds)
         # WARNING: In Pipecat mode (vad_force_turn_endpoint=True), this is
         # automatically set equal to min_turn_silence
         # to avoid double turn detection. Only used as-is in STT mode.
         max_turn_silence=500,
-
         # End of turn confidence threshold (0.0 to 1.0)
         # Higher = requires more confidence before ending turn
         # end_of_turn_confidence_threshold=0.8,
-
         # ====================================================================
         # Prompting & Boosting
         # ====================================================================
-
         # Custom Prompt (WARNING: test carefully, default is optimized!)
         # None = Use AssemblyAI's optimized default (recommended for 88% accuracy)
         prompt=None,
         # prompt="Transcribe speech with focus on technical terms.",
         # prompt="Context: Medical conversation. Transcribe accurately.",
-
         # Keyterms Prompting (boosts recognition for specific words)
         # NOTE: Cannot use both prompt and keyterms_prompt!
         keyterms_prompt=None,
         # keyterms_prompt=["Pipecat", "AssemblyAI", "OpenAI", "Cartesia"],
         # keyterms_prompt=["Python", "JavaScript", "TypeScript", "API"],
-
         # ====================================================================
         # Diarization (Speaker Identification)
         # ====================================================================
-
         # Enable speaker labels (identifies different speakers)
         speaker_labels=None,  # None or True
         # speaker_labels=True,
-
         # ====================================================================
         # Audio Configuration
         # ====================================================================
-
         # Audio sample rate (Hz)
         # sample_rate=16000,
         # sample_rate=8000,
-
         # Audio encoding format
         # encoding="pcm_s16le",  # Default: 16-bit PCM
         # encoding="pcm_mulaw",  # μ-law encoding (telephony)
-
         # ====================================================================
         # Other Options
         # ====================================================================
-
         # Format transcript turns (applies formatting rules)
         # format_turns=True,  # Default
         # format_turns=False,
-
         # Language detection (only for universal-streaming-multilingual)
         # language_detection=True,
     )
 
     # Log connection parameters for debugging
-    logger.info("="*80)
+    logger.info("=" * 80)
     logger.info("CONNECTION PARAMETERS:")
     logger.info(f"  speech_model: {connection_params.speech_model}")
     logger.info(f"  min_turn_silence: {connection_params.min_turn_silence}")
@@ -156,27 +141,26 @@ async def main():
     logger.info(f"  keyterms_prompt: {connection_params.keyterms_prompt}")
     logger.info(f"  speaker_labels: {connection_params.speaker_labels}")
     logger.info(f"  format_turns: {connection_params.format_turns}")
-    logger.info(f"  end_of_turn_confidence_threshold: {connection_params.end_of_turn_confidence_threshold}")
+    logger.info(
+        f"  end_of_turn_confidence_threshold: {connection_params.end_of_turn_confidence_threshold}"
+    )
     logger.info(f"  language_detection: {connection_params.language_detection}")
-    logger.info("="*80)
+    logger.info("=" * 80)
 
     # AssemblyAI Speech-to-Text Service
     stt = AssemblyAISTTService(
         api_key=os.getenv("ASSEMBLYAI_API_KEY"),
         connection_params=connection_params,
-
         # Turn Detection Mode
         # True = Pipecat mode (VAD + Smart Turn controls turns)
         # False = STT mode (u3-rt-pro model controls turns)
         vad_force_turn_endpoint=True,
-
         # Speaker Formatting (only used if speaker_labels=True)
         # None = Just log speaker IDs, don't modify transcript
         speaker_format=None,
         # speaker_format="<Speaker {speaker}>{text}</Speaker {speaker}>",
         # speaker_format="{speaker}: {text}",
         # speaker_format="[{speaker}] {text}",
-
         # Additional available parameters (uncomment to use):
         # should_interrupt=True,  # Only for STT mode
     )