feat: add transcript panel during live call for better visibility (#116)

* chore: remove old signaling route

* Show real time feedbacks

api/app.py

@@ -20,7 +20,6 @@ if SENTRY_DSN and (
     print(f"Sentry initialized in environment: {ENVIRONMENT}")
 
 
-import asyncio
 from contextlib import asynccontextmanager
 from typing import Optional
 
@@ -30,7 +29,6 @@ from fastapi.middleware.cors import CORSMiddleware
 from loguru import logger
 
 from api.routes.main import router as main_router
-from api.routes.rtc_offer import pcs_map
 from api.services.telephony.worker_event_subscriber import (
     WorkerEventSubscriber,
     setup_worker_subscriber,
@@ -77,11 +75,6 @@ async def lifespan(app: FastAPI):
             # Fall back to immediate stop
             await worker_subscriber.stop()
 
-    # close all dangling pipecat connections
-    coros = [pc.close() for pc in pcs_map.values()]
-    await asyncio.gather(*coros)
-    pcs_map.clear()
-
     await redis.aclose()
 
 

api/routes/main.py

@@ -10,7 +10,6 @@ from api.routes.organization_usage import router as organization_usage_router
 from api.routes.public_agent import router as public_agent_router
 from api.routes.public_embed import router as public_embed_router
 from api.routes.reports import router as reports_router
-from api.routes.rtc_offer import router as rtc_offer_router
 from api.routes.s3_signed_url import router as s3_router
 from api.routes.service_keys import router as service_keys_router
 from api.routes.superuser import router as superuser_router
@@ -27,7 +26,6 @@ router = APIRouter(
 )
 
 router.include_router(telephony_router)
-router.include_router(rtc_offer_router)
 router.include_router(superuser_router)
 router.include_router(workflow_router)
 router.include_router(user_router)

api/routes/rtc_offer.py

@@ -1,77 +0,0 @@
-from typing import Dict
-
-from fastapi import APIRouter, BackgroundTasks, Depends
-from loguru import logger
-from pydantic import BaseModel
-
-from api.db.models import UserModel
-from api.services.auth.depends import get_user
-from api.services.pipecat.run_pipeline import run_pipeline_smallwebrtc
-from pipecat.transports.smallwebrtc.connection import SmallWebRTCConnection
-from pipecat.utils.context import set_current_run_id
-
-router = APIRouter(prefix="/pipecat")
-
-pcs_map: Dict[str, SmallWebRTCConnection] = {}
-ice_servers = ["stun:stun.l.google.com:19302"]
-
-
-class RTCOfferRequest(BaseModel):
-    pc_id: str | None
-    sdp: str
-    type: str
-    workflow_id: int
-    workflow_run_id: int
-    restart_pc: bool = False
-    call_context_vars: dict | None = None
-
-
-@router.post("/rtc-offer")
-async def offer(
-    request: RTCOfferRequest,
-    background_tasks: BackgroundTasks,
-    user: UserModel = Depends(get_user),
-):
-    pc_id = request.pc_id
-
-    if pc_id and pc_id in pcs_map:
-        # Ensure run_id context is available for logs even when reusing an existing PC.
-        set_current_run_id(request.workflow_run_id)
-
-        pipecat_connection = pcs_map[pc_id]
-        logger.info(f"Reusing existing connection for pc_id: {pc_id}")
-        await pipecat_connection.renegotiate(
-            sdp=request.sdp,
-            type=request.type,
-            restart_pc=request.restart_pc,
-        )
-    else:
-        # Set the run_id *before* creating the SmallWebRTCConnection so that all
-        # async tasks and event-handler coroutines spawned inside the
-        # constructor inherit the correct context variable value.  Otherwise the
-        # default ("NA") leaks into the log output produced by those tasks.
-        set_current_run_id(request.workflow_run_id)
-
-        pipecat_connection = SmallWebRTCConnection(ice_servers)
-        await pipecat_connection.initialize(sdp=request.sdp, type=request.type)
-
-        @pipecat_connection.event_handler("closed")
-        async def handle_disconnected(webrtc_connection: SmallWebRTCConnection):
-            logger.info(
-                f"In pipecat connection closed handler. Popping peer connection pc_id: {webrtc_connection.pc_id} from pcs_map"
-            )
-            pcs_map.pop(webrtc_connection.pc_id, None)
-
-        background_tasks.add_task(
-            run_pipeline_smallwebrtc,
-            pipecat_connection,
-            request.workflow_id,
-            request.workflow_run_id,
-            user.id,
-            request.call_context_vars or {},
-        )
-
-    answer = pipecat_connection.get_answer()
-    pcs_map[answer["pc_id"]] = pipecat_connection
-
-    return answer

api/routes/webrtc_signaling.py

@@ -18,11 +18,16 @@ from aiortc import RTCIceServer
 from aiortc.sdp import candidate_from_sdp
 from fastapi import APIRouter, Depends, WebSocket, WebSocketDisconnect
 from loguru import logger
+from starlette.websockets import WebSocketState
 
 from api.db import db_client
 from api.db.models import UserModel
 from api.services.auth.depends import get_user_ws
 from api.services.pipecat.run_pipeline import run_pipeline_smallwebrtc
+from api.services.pipecat.ws_sender_registry import (
+    register_ws_sender,
+    unregister_ws_sender,
+)
 from api.services.quota_service import check_dograh_quota
 from pipecat.transports.smallwebrtc.connection import SmallWebRTCConnection
 from pipecat.utils.context import set_current_run_id
@@ -92,6 +97,9 @@ class SignalingManager:
             # Cleanup
             self._connections.pop(connection_id, None)
 
+            # Unregister WebSocket sender for real-time feedback
+            unregister_ws_sender(workflow_run_id)
+
             # Clean up all peer connections for this workflow run
             # Note: In a WebSocket-based signaling approach (vs HTTP PATCH),
             # we maintain our own connection map instead of relying on
@@ -182,6 +190,13 @@ class SignalingManager:
             # Store peer connection using client's pc_id
             self._peer_connections[pc_id] = pc
 
+            # Register WebSocket sender for real-time feedback
+            async def ws_sender(message: dict):
+                if ws.application_state == WebSocketState.CONNECTED:
+                    await ws.send_json(message)
+
+            register_ws_sender(workflow_run_id, ws_sender)
+
             # Setup closed handler
             @pc.event_handler("closed")
             async def handle_disconnected(webrtc_connection: SmallWebRTCConnection):

api/services/pipecat/realtime_feedback_observer.py

@@ -0,0 +1,227 @@
+"""Real-time feedback observer for sending pipeline events to the frontend.
+
+This observer watches pipeline frames and sends relevant events (transcriptions,
+bot text) over WebSocket to provide real-time feedback in the UI.
+
+For frames with presentation timestamps (pts), like TTSTextFrame, we respect
+the timing by queuing them and sending at the appropriate time, similar to
+how base_output.py handles timed frames.
+"""
+
+import asyncio
+import time
+from typing import Awaitable, Callable, Optional, Set
+
+from loguru import logger
+
+from pipecat.frames.frames import (
+    CancelFrame,
+    EndFrame,
+    FunctionCallInProgressFrame,
+    FunctionCallResultFrame,
+    InterimTranscriptionFrame,
+    InterruptionFrame,
+    StopFrame,
+    TranscriptionFrame,
+    TTSTextFrame,
+)
+from pipecat.observers.base_observer import BaseObserver, FramePushed
+from pipecat.processors.frame_processor import FrameDirection
+from pipecat.utils.time import nanoseconds_to_seconds
+
+
+class RealtimeFeedbackObserver(BaseObserver):
+    """Observer that sends real-time transcription and bot response events via WebSocket.
+
+    For frames with pts (presentation timestamp), we queue them and send at the
+    appropriate time to sync with audio playback.
+    """
+
+    def __init__(
+        self,
+        ws_sender: Callable[[dict], Awaitable[None]],
+    ):
+        """
+        Args:
+            ws_sender: Async function to send messages over WebSocket.
+                       Expected signature: async def send(message: dict) -> None
+        """
+        super().__init__()
+        self._ws_sender = ws_sender
+        self._frames_seen: Set[str] = set()
+
+        # Clock/timing for pts-based frames (similar to base_output.py)
+        self._clock_queue: Optional[asyncio.PriorityQueue] = None
+        self._clock_task: Optional[asyncio.Task] = None
+        self._clock_start_time: Optional[float] = (
+            None  # Wall clock time when we started
+        )
+        self._pts_start_time: Optional[int] = None  # First pts value we saw
+
+    async def _ensure_clock_task(self):
+        """Create the clock task if it doesn't exist."""
+        if self._clock_queue is None:
+            self._clock_queue = asyncio.PriorityQueue()
+            self._clock_task = asyncio.create_task(self._clock_task_handler())
+
+    async def _cancel_clock_task(self):
+        """Cancel the clock task and clear the queue.
+
+        Called on interruption to discard any pending bot text that
+        hasn't been sent yet.
+        """
+        if self._clock_task:
+            self._clock_task.cancel()
+            try:
+                await self._clock_task
+            except asyncio.CancelledError:
+                pass
+            self._clock_task = None
+        self._clock_queue = None
+        # Reset timing references so next bot response starts fresh
+        self._clock_start_time = None
+        self._pts_start_time = None
+
+    async def _handle_interruption(self):
+        """Handle interruption by clearing queued bot text.
+
+        Similar to base_output.py's handle_interruptions, we cancel the
+        clock task and recreate it to discard pending frames.
+        """
+        await self._cancel_clock_task()
+
+    async def _clock_task_handler(self):
+        """Process timed frames from the queue, respecting their presentation timestamps.
+
+        Similar to base_output.py's _clock_task_handler, we wait until the
+        frame's pts time has arrived before sending.
+        """
+        while True:
+            try:
+                pts, _frame_id, message = await self._clock_queue.get()
+
+                # Calculate when to send based on pts relative to our start time
+                if (
+                    self._clock_start_time is not None
+                    and self._pts_start_time is not None
+                ):
+                    # Target time = start wall time + (frame pts - start pts) in seconds
+                    target_time = self._clock_start_time + nanoseconds_to_seconds(
+                        pts - self._pts_start_time
+                    )
+                    current_time = time.time()
+                    if target_time > current_time:
+                        await asyncio.sleep(target_time - current_time)
+
+                # Send the message
+                await self._send_message(message)
+                self._clock_queue.task_done()
+            except asyncio.CancelledError:
+                break
+            except Exception as e:
+                logger.debug(f"Clock task error: {e}")
+
+    async def on_push_frame(self, data: FramePushed):
+        """Process frames and send relevant ones to the client."""
+        frame = data.frame
+        frame_direction = data.direction
+
+        # Handle pipeline termination - stop clock task
+        if isinstance(frame, (EndFrame, CancelFrame, StopFrame)):
+            await self._cancel_clock_task()
+            return
+
+        # Handle interruptions - clear any queued bot text
+        if isinstance(frame, InterruptionFrame):
+            await self._handle_interruption()
+            return
+
+        # Skip already processed frames (frames can be observed multiple times)
+        if frame.id in self._frames_seen:
+            return
+        self._frames_seen.add(frame.id)
+
+        # Handle user transcriptions (interim)
+        if isinstance(frame, InterimTranscriptionFrame):
+            await self._send_message(
+                {
+                    "type": "rtf-user-transcription",
+                    "payload": {
+                        "text": frame.text,
+                        "final": False,
+                        "user_id": frame.user_id,
+                        "timestamp": frame.timestamp,
+                    },
+                }
+            )
+        # Handle user transcriptions (final)
+        elif isinstance(frame, TranscriptionFrame):
+            await self._send_message(
+                {
+                    "type": "rtf-user-transcription",
+                    "payload": {
+                        "text": frame.text,
+                        "final": True,
+                        "user_id": frame.user_id,
+                        "timestamp": frame.timestamp,
+                    },
+                }
+            )
+        # Handle bot TTS text - respect pts timing
+        elif isinstance(frame, TTSTextFrame):
+            message = {
+                "type": "rtf-bot-text",
+                "payload": {
+                    "text": frame.text,
+                },
+            }
+
+            # If frame has pts, queue it for timed delivery
+            if frame.pts:
+                # Initialize timing reference on first pts frame
+                if self._pts_start_time is None:
+                    self._pts_start_time = frame.pts
+                    self._clock_start_time = time.time()
+
+                await self._ensure_clock_task()
+                await self._clock_queue.put((frame.pts, frame.id, message))
+            else:
+                # No pts, send immediately
+                await self._send_message(message)
+        # Handle function call in progress
+        elif (
+            isinstance(frame, FunctionCallInProgressFrame)
+            and frame_direction == FrameDirection.DOWNSTREAM
+        ):
+            await self._send_message(
+                {
+                    "type": "rtf-function-call-start",
+                    "payload": {
+                        "function_name": frame.function_name,
+                        "tool_call_id": frame.tool_call_id,
+                    },
+                }
+            )
+        # Handle function call result
+        elif (
+            isinstance(frame, FunctionCallResultFrame)
+            and frame_direction == FrameDirection.DOWNSTREAM
+        ):
+            await self._send_message(
+                {
+                    "type": "rtf-function-call-end",
+                    "payload": {
+                        "function_name": frame.function_name,
+                        "tool_call_id": frame.tool_call_id,
+                        "result": str(frame.result) if frame.result else None,
+                    },
+                }
+            )
+
+    async def _send_message(self, message: dict):
+        """Send message via WebSocket, handling errors gracefully."""
+        try:
+            await self._ws_sender(message)
+        except Exception as e:
+            # Log but don't fail - feedback is non-critical
+            logger.debug(f"Failed to send real-time feedback message: {e}")

api/services/pipecat/run_pipeline.py

@@ -23,6 +23,7 @@ from api.services.pipecat.pipeline_engine_callbacks_processor import (
     PipelineEngineCallbacksProcessor,
 )
 from api.services.pipecat.pipeline_metrics_aggregator import PipelineMetricsAggregator
+from api.services.pipecat.realtime_feedback_observer import RealtimeFeedbackObserver
 from api.services.pipecat.service_factory import (
     create_llm_service,
     create_stt_service,
@@ -38,6 +39,7 @@ from api.services.pipecat.transport_setup import (
     create_vonage_transport,
     create_webrtc_transport,
 )
+from api.services.pipecat.ws_sender_registry import get_ws_sender
 from api.services.telephony.stasis_rtp_connection import StasisRTPConnection
 from api.services.workflow.dto import ReactFlowDTO
 from api.services.workflow.pipecat_engine import PipecatEngine
@@ -564,6 +566,12 @@ async def _run_pipeline(
     # Create pipeline task with audio configuration
     task = create_pipeline_task(pipeline, workflow_run_id, audio_config)
 
+    # Add real-time feedback observer if WebSocket sender is available
+    ws_sender = get_ws_sender(workflow_run_id)
+    if ws_sender:
+        feedback_observer = RealtimeFeedbackObserver(ws_sender=ws_sender)
+        task.add_observer(feedback_observer)
+
     # Now set the task on the engine
     engine.set_task(task)
 

api/services/pipecat/ws_sender_registry.py

@@ -0,0 +1,28 @@
+"""Registry to store WebSocket senders by workflow_run_id.
+
+This allows the pipeline observer to send messages back through
+the signaling WebSocket without passing the WebSocket directly.
+"""
+
+from typing import Awaitable, Callable, Dict, Optional
+
+_ws_senders: Dict[int, Callable[[dict], Awaitable[None]]] = {}
+
+
+def register_ws_sender(
+    workflow_run_id: int, sender: Callable[[dict], Awaitable[None]]
+) -> None:
+    """Register a WebSocket sender for a workflow run."""
+    _ws_senders[workflow_run_id] = sender
+
+
+def unregister_ws_sender(workflow_run_id: int) -> None:
+    """Unregister a WebSocket sender for a workflow run."""
+    _ws_senders.pop(workflow_run_id, None)
+
+
+def get_ws_sender(
+    workflow_run_id: int,
+) -> Optional[Callable[[dict], Awaitable[None]]]:
+    """Get the WebSocket sender for a workflow run."""
+    return _ws_senders.get(workflow_run_id)