feat: add optional bot backchannels to prompt pipelines

backend/services/pipecat/pipeline.py

@@ -14,6 +14,7 @@ from models import AssistantConfig
 from services.brains import Brain, BrainRuntime, build_brain
 from services.brains.base import RealtimeBrainRuntime
 from services.conversation_history import ConversationRecorder
+from services.pipecat.backchannel import BotBackchannelProcessor
 from services.pipecat.call_lifecycle import (
     CallEndCoordinator,
     EndCallAfterSpeechProcessor,
@@ -722,6 +723,14 @@ async def run_pipeline(
         protocol_adapter.inference_processors() if protocol_adapter else []
     )
     protocol_outputs = protocol_adapter.output_processors() if protocol_adapter else []
+    backchannel_config = cfg.turnConfig.get("bot_backchannel", cfg.turnConfig.get("botBackchannel", {}))
+    backchannel_processors = []
+    if cfg.type == "prompt" and backchannel_config.get("enabled", False):
+        backchannel_processors.append(BotBackchannelProcessor(
+            delay_secs=float(backchannel_config.get("delay_secs", backchannel_config.get("delaySecs", 4))),
+            can_speak=lambda: (call_end.accepts_input and not call_end.ending
+                               and input_state["enabled"] and not tool_interruption_strategy.is_muted),
+        ))
     pipeline = Pipeline(
         [
             transport.input(),
@@ -740,6 +749,7 @@ async def run_pipeline(
             # Pipecat commits the generated prefix immediately instead of
             # waiting for a TTS provider to emit spoken-text/timestamp frames.
             assistant_aggregator,
+            *backchannel_processors,
             tts_processor,
             EndCallAfterSpeechProcessor(call_end),
             ConversationHistoryProcessor(recorder),