From f1a5aa40d693679c3dc7aa635432b1be27ab8159 Mon Sep 17 00:00:00 2001 From: Abhishek Kumar Date: Sat, 4 Apr 2026 19:35:52 +0530 Subject: [PATCH] feat: add pre call fetch configuration --- api/services/pipecat/event_handlers.py | 44 ++++++ api/services/pipecat/pre_call_fetch.py | 115 +++++++++++++++ api/services/pipecat/run_pipeline.py | 24 +++ api/services/workflow/dto.py | 4 + api/services/workflow/pipecat_engine.py | 2 - .../workflow/pipecat_engine_custom_tools.py | 51 +------ api/services/workflow/workflow.py | 3 + .../test_pipecat_engine_context_update.py | 1 + api/tests/test_pipecat_engine_end_call.py | 9 ++ ...cat_engine_node_switch_with_user_speech.py | 1 + api/tests/test_pipecat_engine_tool_calls.py | 1 + ...test_pipecat_engine_variable_extraction.py | 1 + ...t_tts_endframe_with_audio_write_failure.py | 2 + api/tests/test_user_idle_handler.py | 1 + .../test_user_muting_during_bot_speech.py | 3 + api/utils/hold_audio.py | 61 +++++++- docs/docs.json | 3 + docs/images/embedding-configurations.png | Bin 0 -> 59229 bytes docs/voice-agent/knowledge-base.mdx | 53 +++++++ docs/voice-agent/pre-call-data-fetch.mdx | 139 ++++++++++++++++++ docs/voice-agent/tools/introduction.mdx | 39 +++++ ui/src/components/flow/DocumentSelector.tsx | 44 ++++-- ui/src/components/flow/ToolSelector.tsx | 4 +- ui/src/components/flow/nodes/StartCall.tsx | 95 +++++++++++- ui/src/components/flow/types.ts | 4 + ui/src/constants/documentation.ts | 6 + 26 files changed, 644 insertions(+), 66 deletions(-) create mode 100644 api/services/pipecat/pre_call_fetch.py create mode 100644 docs/images/embedding-configurations.png create mode 100644 docs/voice-agent/knowledge-base.mdx create mode 100644 docs/voice-agent/pre-call-data-fetch.mdx create mode 100644 docs/voice-agent/tools/introduction.mdx diff --git a/api/services/pipecat/event_handlers.py b/api/services/pipecat/event_handlers.py index 55bc0b4..70d8935 100644 --- a/api/services/pipecat/event_handlers.py +++ b/api/services/pipecat/event_handlers.py @@ -1,3 +1,5 @@ +import asyncio + from loguru import logger from api.db import db_client @@ -13,6 +15,7 @@ from api.services.pipecat.tracing_config import get_trace_url from api.services.workflow.pipecat_engine import PipecatEngine from api.tasks.arq import enqueue_job from api.tasks.function_names import FunctionNames +from api.utils.hold_audio import play_hold_audio_loop from pipecat.frames.frames import Frame, LLMContextFrame, TTSSpeakFrame from pipecat.pipeline.task import PipelineTask from pipecat.processors.audio.audio_buffer_processor import AudioBufferProcessor @@ -28,6 +31,7 @@ def register_event_handlers( in_memory_logs_buffer: InMemoryLogsBuffer, pipeline_metrics_aggregator: PipelineMetricsAggregator, audio_config=AudioConfig, + pre_call_fetch_task: asyncio.Task | None = None, ): """Register all event handlers for transport and task events. @@ -58,6 +62,9 @@ def register_event_handlers( async def maybe_trigger_initial_response(): """Start the conversation after both pipeline_started and client_connected events. + If a pre-call fetch is in progress, plays a ringer while waiting for the + response, then merges the result into the call context before proceeding. + If the start node has a greeting configured, play it directly via TTS. Otherwise, trigger an LLM generation for the opening message. """ @@ -68,6 +75,43 @@ def register_event_handlers( ): ready_state["initial_response_triggered"] = True + # Wait for pre-call fetch if in progress, playing ringer meanwhile + if pre_call_fetch_task is not None: + if not pre_call_fetch_task.done(): + logger.info( + "Pre-call fetch still in progress, playing ringer while waiting" + ) + stop_ringer = asyncio.Event() + sample_rate = audio_config.pipeline_sample_rate or 16000 + ringer_task = asyncio.create_task( + play_hold_audio_loop(task, stop_ringer, sample_rate) + ) + try: + fetch_result = await pre_call_fetch_task + finally: + stop_ringer.set() + await ringer_task + else: + fetch_result = pre_call_fetch_task.result() + + if fetch_result: + engine._call_context_vars.update(fetch_result) + try: + await db_client.update_workflow_run( + workflow_run_id, + initial_context={**engine._call_context_vars}, + ) + except Exception as e: + logger.error(f"Failed to persist pre-call fetch context: {e}") + logger.info( + f"Pre-call fetch complete, merged keys: " + f"{list(fetch_result.keys())}" + ) + + # Set the start node now (after pre-call fetch data is merged) + # so that render_template() has the complete _call_context_vars. + await engine.set_node(engine.workflow.start_node_id) + greeting = engine.get_start_greeting() if greeting: logger.debug( diff --git a/api/services/pipecat/pre_call_fetch.py b/api/services/pipecat/pre_call_fetch.py new file mode 100644 index 0000000..7776111 --- /dev/null +++ b/api/services/pipecat/pre_call_fetch.py @@ -0,0 +1,115 @@ +"""Pre-call HTTP data fetch for StartCall node. + +Executes an HTTP request before a voice call starts to enrich the +call context with data from external systems (CRM, ERP, etc.). +""" + +from typing import Any, Dict, Optional + +import httpx +from loguru import logger + +from api.db import db_client +from api.utils.credential_auth import build_auth_header + +PRE_CALL_FETCH_TIMEOUT_SECONDS = 10 + + +async def execute_pre_call_fetch( + *, + url: str, + credential_uuid: Optional[str], + call_context_vars: Dict[str, Any], + workflow_id: int, + organization_id: int, +) -> Dict[str, Any]: + """Execute a POST request to fetch data before a call starts. + + Sends a standardized payload with call metadata (agent_id, from/to numbers). + The response JSON is returned as a dict to be merged into initial_context. + + Returns: + Response JSON dict on success, empty dict on any failure. + Never raises. + """ + # Build standardized payload + payload = { + "event": "call_inbound", + "call_inbound": { + "agent_id": workflow_id, + "from_number": call_context_vars.get("caller_number", ""), + "to_number": call_context_vars.get("called_number", ""), + }, + } + + # Build headers + headers: Dict[str, str] = {"Content-Type": "application/json"} + + if credential_uuid: + try: + credential = await db_client.get_credential_by_uuid( + credential_uuid, organization_id + ) + if credential: + headers.update(build_auth_header(credential)) + else: + logger.warning( + f"Pre-call fetch: credential {credential_uuid} not found" + ) + except Exception as e: + logger.error(f"Pre-call fetch: failed to resolve credential: {e}") + + logger.info(f"Pre-call fetch: POST {url}") + + try: + async with httpx.AsyncClient(timeout=PRE_CALL_FETCH_TIMEOUT_SECONDS) as client: + response = await client.post(url, headers=headers, json=payload) + + try: + response_data = response.json() + except Exception: + response_data = {} + + if response.is_success: + if not isinstance(response_data, dict): + logger.warning( + "Pre-call fetch: response is not a JSON object, skipping" + ) + return {} + + # Extract dynamic_variables from Retell-compatible response + # Supports: {call_inbound: {dynamic_variables: {...}}} + # or: {dynamic_variables: {...}} + dynamic_vars = {} + call_inbound = response_data.get("call_inbound") + if isinstance(call_inbound, dict): + dynamic_vars = call_inbound.get("dynamic_variables", {}) + elif "dynamic_variables" in response_data: + dynamic_vars = response_data["dynamic_variables"] + + if not isinstance(dynamic_vars, dict): + dynamic_vars = {} + + logger.info( + f"Pre-call fetch: success ({response.status_code}), " + f"dynamic_variables keys: {list(dynamic_vars.keys())}" + ) + return dynamic_vars + else: + logger.warning( + f"Pre-call fetch: HTTP {response.status_code} - " + f"{response.text[:200]}" + ) + return {} + + except httpx.TimeoutException: + logger.error( + f"Pre-call fetch: timed out after {PRE_CALL_FETCH_TIMEOUT_SECONDS}s" + ) + return {} + except httpx.RequestError as e: + logger.error(f"Pre-call fetch: request failed: {e}") + return {} + except Exception as e: + logger.error(f"Pre-call fetch: unexpected error: {e}") + return {} diff --git a/api/services/pipecat/run_pipeline.py b/api/services/pipecat/run_pipeline.py index df9b02f..82ea3d1 100644 --- a/api/services/pipecat/run_pipeline.py +++ b/api/services/pipecat/run_pipeline.py @@ -24,6 +24,7 @@ from api.services.pipecat.pipeline_engine_callbacks_processor import ( PipelineEngineCallbacksProcessor, ) from api.services.pipecat.pipeline_metrics_aggregator import PipelineMetricsAggregator +from api.services.pipecat.pre_call_fetch import execute_pre_call_fetch from api.services.pipecat.realtime_feedback_observer import ( RealtimeFeedbackObserver, register_turn_log_handlers, @@ -622,6 +623,28 @@ async def _run_pipeline( ReactFlowDTO.model_validate(workflow.workflow_definition_with_fallback) ) + # Pre-call fetch: fire early so it runs concurrently with remaining setup + pre_call_fetch_task = None + start_node = workflow_graph.nodes.get(workflow_graph.start_node_id) + if ( + start_node + and start_node.pre_call_fetch_enabled + and start_node.pre_call_fetch_url + ): + logger.info( + f"Pre-call fetch enabled for workflow run {workflow_run_id}, " + f"firing request to {start_node.pre_call_fetch_url}" + ) + pre_call_fetch_task = asyncio.create_task( + execute_pre_call_fetch( + url=start_node.pre_call_fetch_url, + credential_uuid=start_node.pre_call_fetch_credential_uuid, + call_context_vars=merged_call_context_vars, + workflow_id=workflow_id, + organization_id=workflow.organization_id, + ) + ) + # Create in-memory logs buffer early so it can be used by engine callbacks in_memory_logs_buffer = InMemoryLogsBuffer(workflow_run_id) @@ -952,6 +975,7 @@ async def _run_pipeline( in_memory_logs_buffer=in_memory_logs_buffer, pipeline_metrics_aggregator=pipeline_metrics_aggregator, audio_config=audio_config, + pre_call_fetch_task=pre_call_fetch_task, ) register_audio_data_handler(audio_buffer, workflow_run_id, in_memory_audio_buffer) diff --git a/api/services/workflow/dto.py b/api/services/workflow/dto.py index 3fc3119..31d9a35 100644 --- a/api/services/workflow/dto.py +++ b/api/services/workflow/dto.py @@ -59,6 +59,10 @@ class NodeDataDTO(BaseModel): detect_voicemail: bool = False delayed_start: bool = False delayed_start_duration: Optional[float] = None + # Pre-call fetch (start node only) + pre_call_fetch_enabled: bool = False + pre_call_fetch_url: Optional[str] = None + pre_call_fetch_credential_uuid: Optional[str] = None tool_uuids: Optional[List[str]] = None document_uuids: Optional[List[str]] = None trigger_path: Optional[str] = None diff --git a/api/services/workflow/pipecat_engine.py b/api/services/workflow/pipecat_engine.py index 1b56c0d..bf5c0d9 100644 --- a/api/services/workflow/pipecat_engine.py +++ b/api/services/workflow/pipecat_engine.py @@ -162,8 +162,6 @@ class PipecatEngine: if self._context_compaction_enabled: self._context_summarization_manager = ContextSummarizationManager(self) - await self.set_node(self.workflow.start_node_id) - logger.debug(f"{self.__class__.__name__} initialized") except Exception as e: logger.error(f"Error initializing {self.__class__.__name__}: {e}") diff --git a/api/services/workflow/pipecat_engine_custom_tools.py b/api/services/workflow/pipecat_engine_custom_tools.py index b0dd1c0..eecb338 100644 --- a/api/services/workflow/pipecat_engine_custom_tools.py +++ b/api/services/workflow/pipecat_engine_custom_tools.py @@ -14,7 +14,6 @@ from typing import TYPE_CHECKING, Any, Dict, List, Optional from loguru import logger -from api.constants import APP_ROOT_DIR from api.db import db_client from api.enums import ToolCategory, WorkflowRunMode from api.services.telephony.call_transfer_manager import get_call_transfer_manager @@ -28,11 +27,10 @@ from api.services.workflow.tools.custom_tool import ( execute_http_tool, tool_to_function_schema, ) -from api.utils.hold_audio import load_hold_audio +from api.utils.hold_audio import play_hold_audio_loop from pipecat.adapters.schemas.function_schema import FunctionSchema from pipecat.frames.frames import ( FunctionCallResultProperties, - OutputAudioRawFrame, TTSSpeakFrame, ) from pipecat.services.llm_service import FunctionCallParams @@ -539,7 +537,11 @@ class CustomToolManager: # Start hold music as background task hold_music_task = asyncio.create_task( - self.play_hold_music_loop(hold_music_stop_event, sample_rate) + play_hold_audio_loop( + self._engine.task, + hold_music_stop_event, + sample_rate, + ) ) # Wait for transfer completion using Redis pub/sub @@ -666,44 +668,3 @@ class CustomToolManager: # Unknown action, treat as generic success logger.warning(f"Unknown transfer action: {action}, treating as success") await function_call_params.result_callback(result) - - async def play_hold_music_loop( - self, stop_event: asyncio.Event, sample_rate: int = 8000 - ): - """Play hold music in a loop until stop event is triggered. - - Args: - stop_event: Event to stop the hold music loop - sample_rate: Sample rate for the hold music (default 8000Hz for Twilio) - """ - try: - # Path to hold music file based on sample rate - hold_music_file = ( - APP_ROOT_DIR / "assets" / f"transfer_hold_ring_{sample_rate}.wav" - ) - hold_audio_data = load_hold_audio(hold_music_file, sample_rate) - num_samples = len(hold_audio_data) // 2 - duration = int(num_samples / sample_rate) - - logger.info(f"Starting hold music loop with file: {hold_music_file}") - - while not stop_event.is_set(): - # Queue the hold audio frame - frame = OutputAudioRawFrame( - audio=hold_audio_data, - sample_rate=sample_rate, - num_channels=1, - ) - await self._engine.task.queue_frame(frame) - - # Wait for the audio to play or until stopped - try: - await asyncio.wait_for(stop_event.wait(), timeout=duration + 1.5) - break # Stop event was set - except asyncio.TimeoutError: - pass # Continue looping - - logger.info("Hold music loop stopped") - - except Exception as e: - logger.error(f"Error in hold music loop: {e}") diff --git a/api/services/workflow/workflow.py b/api/services/workflow/workflow.py index 3278685..fe5a9ec 100644 --- a/api/services/workflow/workflow.py +++ b/api/services/workflow/workflow.py @@ -82,6 +82,9 @@ class Node: self.delayed_start_duration = data.delayed_start_duration self.tool_uuids = data.tool_uuids self.document_uuids = data.document_uuids + self.pre_call_fetch_enabled = data.pre_call_fetch_enabled + self.pre_call_fetch_url = data.pre_call_fetch_url + self.pre_call_fetch_credential_uuid = data.pre_call_fetch_credential_uuid self.data = data diff --git a/api/tests/test_pipecat_engine_context_update.py b/api/tests/test_pipecat_engine_context_update.py index 30dd4b8..8ef0e0e 100644 --- a/api/tests/test_pipecat_engine_context_update.py +++ b/api/tests/test_pipecat_engine_context_update.py @@ -201,6 +201,7 @@ async def run_pipeline_and_capture_context( async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) diff --git a/api/tests/test_pipecat_engine_end_call.py b/api/tests/test_pipecat_engine_end_call.py index 78bb020..7ef7ffe 100644 --- a/api/tests/test_pipecat_engine_end_call.py +++ b/api/tests/test_pipecat_engine_end_call.py @@ -287,6 +287,7 @@ class TestEndCallViaNodeTransition: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) @@ -390,6 +391,7 @@ class TestEndCallViaNodeTransition: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) @@ -488,6 +490,7 @@ class TestEndCallViaCustomTool: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) @@ -579,6 +582,7 @@ class TestEndCallViaCustomTool: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) @@ -656,6 +660,7 @@ class TestEndCallViaClientDisconnect: async def initialize_and_disconnect(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) # Wait for initial generation to complete @@ -746,6 +751,7 @@ class TestEndCallRaceConditions: async def initialize_and_race(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) # Wait for initial generation @@ -858,6 +864,7 @@ class TestEndCallRaceConditions: nonlocal disconnect_called await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) # Wait for the end_call tool to be called @@ -951,6 +958,7 @@ class TestEndCallExtractionBehavior: async def initialize_and_end(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) # Wait for initial generation @@ -1076,6 +1084,7 @@ class TestEndCallExtractionBehavior: async def initialize_and_end(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) # Wait for initial generation diff --git a/api/tests/test_pipecat_engine_node_switch_with_user_speech.py b/api/tests/test_pipecat_engine_node_switch_with_user_speech.py index efad8fd..205baa1 100644 --- a/api/tests/test_pipecat_engine_node_switch_with_user_speech.py +++ b/api/tests/test_pipecat_engine_node_switch_with_user_speech.py @@ -294,6 +294,7 @@ class TestNodeSwitchWithUserSpeech: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) # Start the LLM generation - user speech will be injected # automatically when FunctionCallResultFrame #1 is seen await engine.llm.queue_frame(LLMContextFrame(engine.context)) diff --git a/api/tests/test_pipecat_engine_tool_calls.py b/api/tests/test_pipecat_engine_tool_calls.py index ea4d222..001de29 100644 --- a/api/tests/test_pipecat_engine_tool_calls.py +++ b/api/tests/test_pipecat_engine_tool_calls.py @@ -131,6 +131,7 @@ async def run_pipeline_with_tool_calls( # Small delay to let runner start await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) # Run both concurrently diff --git a/api/tests/test_pipecat_engine_variable_extraction.py b/api/tests/test_pipecat_engine_variable_extraction.py index 8a51614..140c5e8 100644 --- a/api/tests/test_pipecat_engine_variable_extraction.py +++ b/api/tests/test_pipecat_engine_variable_extraction.py @@ -176,6 +176,7 @@ class TestVariableExtractionDuringTransitions: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) diff --git a/api/tests/test_tts_endframe_with_audio_write_failure.py b/api/tests/test_tts_endframe_with_audio_write_failure.py index fa0dba6..d4eb92f 100644 --- a/api/tests/test_tts_endframe_with_audio_write_failure.py +++ b/api/tests/test_tts_endframe_with_audio_write_failure.py @@ -227,6 +227,7 @@ class TestTTSPauseWithAudioWriteFailure: async def initialize_and_end_call(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) # Start LLM generation - this will trigger TTS await engine.llm.queue_frame(LLMContextFrame(engine.context)) @@ -346,6 +347,7 @@ class TestTTSPauseWithAudioWriteFailure: async def initialize_and_observe(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) diff --git a/api/tests/test_user_idle_handler.py b/api/tests/test_user_idle_handler.py index 4548ca7..7c80e7d 100644 --- a/api/tests/test_user_idle_handler.py +++ b/api/tests/test_user_idle_handler.py @@ -274,6 +274,7 @@ class TestUserIdleHandler: async def initialize_engine(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) await engine.llm.queue_frame(LLMContextFrame(engine.context)) await asyncio.gather(run_pipeline(), initialize_engine()) diff --git a/api/tests/test_user_muting_during_bot_speech.py b/api/tests/test_user_muting_during_bot_speech.py index 6fd6b78..ee14234 100644 --- a/api/tests/test_user_muting_during_bot_speech.py +++ b/api/tests/test_user_muting_during_bot_speech.py @@ -266,6 +266,7 @@ class TestUserMutingDuringBotSpeech: async def run_test(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) # Trigger first LLM completion await engine.llm.queue_frame(LLMContextFrame(engine.context)) @@ -356,6 +357,7 @@ class TestUserMutingDuringBotSpeech: async def run_test(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) # Trigger first LLM completion await engine.llm.queue_frame(LLMContextFrame(engine.context)) @@ -451,6 +453,7 @@ class TestUserMutingDuringBotSpeech: async def run_test(): await asyncio.sleep(0.01) await engine.initialize() + await engine.set_node(engine.workflow.start_node_id) # Trigger first LLM completion await engine.llm.queue_frame(LLMContextFrame(engine.context)) diff --git a/api/utils/hold_audio.py b/api/utils/hold_audio.py index e77f24f..c914082 100644 --- a/api/utils/hold_audio.py +++ b/api/utils/hold_audio.py @@ -1,15 +1,19 @@ """ -Hold audio utility for loading and caching hold music files. +Hold audio utility for loading, caching, and playing hold music files. This module provides functionality to load hold music audio files at specific sample rates -with caching to improve performance during multiple calls. +with caching to improve performance during multiple calls, and a reusable loop that queues +audio frames until a stop event is set. """ +import asyncio from typing import Dict, Optional, Tuple import numpy as np from loguru import logger +from pipecat.frames.frames import OutputAudioRawFrame + try: import soundfile as sf except ModuleNotFoundError as e: @@ -92,3 +96,56 @@ def get_cache_info() -> Dict[str, int]: "cached_files": len(_hold_audio_cache), "total_cache_size": sum(len(data) for data in _hold_audio_cache.values()), } + + +async def play_hold_audio_loop( + task, + stop_event: asyncio.Event, + sample_rate: int = 16000, + hold_music_file: Optional[str] = None, +) -> None: + """Play hold/ring-back audio in a loop until *stop_event* is set. + + This is a shared helper used by call-transfer hold music and the + pre-call data fetch ringer. The caller is responsible for creating + the ``asyncio.Event`` and setting it when playback should stop. + + Args: + task: A ``PipelineTask`` (or anything with ``queue_frame``). + stop_event: Set this event to terminate the loop. + sample_rate: Target sample rate for audio playback. + hold_music_file: Path to a WAV file. When *None* the default + ``transfer_hold_ring_{sample_rate}.wav`` asset is used. + """ + if hold_music_file is None: + from api.constants import APP_ROOT_DIR + + hold_music_file = str( + APP_ROOT_DIR / "assets" / f"transfer_hold_ring_{sample_rate}.wav" + ) + + hold_audio_data = load_hold_audio(hold_music_file, sample_rate) + if not hold_audio_data: + logger.warning(f"Hold audio loop: failed to load {hold_music_file}, skipping") + return + + num_samples = len(hold_audio_data) // 2 # 16-bit PCM = 2 bytes per sample + duration = num_samples / sample_rate + + logger.debug(f"Hold audio loop: playing at {sample_rate}Hz") + try: + while not stop_event.is_set(): + frame = OutputAudioRawFrame( + audio=hold_audio_data, + sample_rate=sample_rate, + num_channels=1, + ) + await task.queue_frame(frame) + try: + await asyncio.wait_for(stop_event.wait(), timeout=duration + 1.5) + break + except asyncio.TimeoutError: + pass + except Exception as e: + logger.error(f"Hold audio loop: error: {e}") + logger.debug("Hold audio loop: stopped") diff --git a/docs/docs.json b/docs/docs.json index 89a76f1..3a036e8 100644 --- a/docs/docs.json +++ b/docs/docs.json @@ -56,9 +56,11 @@ "voice-agent/editing-a-workflow", "voice-agent/pre-recorded-audio", "voice-agent/template-variables", + "voice-agent/pre-call-data-fetch", { "group": "Tools", "pages": [ + "voice-agent/tools/introduction", { "group": "Built-in Tools", "pages": [ @@ -74,6 +76,7 @@ } ] }, + "voice-agent/knowledge-base", { "group": "Nodes", "pages": [ diff --git a/docs/images/embedding-configurations.png b/docs/images/embedding-configurations.png new file mode 100644 index 0000000000000000000000000000000000000000..13346fb298b00d6d169abf936e93717be3b9670d GIT binary patch literal 59229 zcmd?QWl)^k5;jVZU?I3`@Zc5*?(Ps^a0Vy1I|O%kw-88hcL?rIu;6aNeIR@<+s--r zyZ`U4x>ZwCGqc`V(yLdm?&s+aQ&NybK_Wncf`USkmJ(Bef`YMtf`Ya}cnSPs#&(zo z1@$7>;seMDBrnHfWNXa?Hnuf1VREy!1KOdW_ypbTz($rPPGp8AW)?R5j1sq&yrh@cc~V+^nr^9C_UM$^Yn= 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zEe6dVYLak>#EOPU_t(GQc121KfGx623X%XqozI_qyDmlPZ+MIL6s~moTmrT=jze5s zz2-3@zv7Bko6bKZw8hhxY83Nx|J=hD&Rcypd+$U;al}wUXNGPxzl66s3xtZs#t5$Y z^z^YLO1ASBP~7Fdr)ZrpcbDzPxtEOkBaR#`CnC7zBF(N(({mt)gbPj`*W^U%ea}yT z!SS8$dpYYb-7KiegV?g)@mO&EB@1|ym;~xT{HrsVeBJ@u-xmp*6S1hn{k2$p0|Tj4 z@X&E^=pN!i$J*Wm-W1yBBQpCnAU@v+%v#cn)g$i}`2h&~ zGkz#EaT+2=ELPTgd!TKd4@6kr>EDRp$3Klj>EZr}R%=60vY+uqi|_NgB3B?Nc(C{8 zdi*z;!+sw2LmKrRW~UU02|PFP&+wguPzB{v`;&QZ#V94ad2k~@h4-Hh-@pHqv4mGX-UGq(Tqla>exdf@V%l=$C?1@wDT;NRiEe3JGSc)P^rr~MD1 zk$+np`o-pOR{v=k>KR;wblvC40OBZvGTHz5I>)emc|DH*?|1&+z#=@6|2MGzzpdE)+P&*(SRlfCer9alaxwk5 zs>}Jv%lKH>IJiW#D6eDik2qecqkm!k^g;TA4AuX8 +You must configure an embedding provider and API key in **AI Models Configuration → Embedding** before using the Knowledge Base. Document processing and retrieval depend on embeddings, so this feature will not work without a valid embedding configuration. + + +![Embedding Configuration](../images/embedding-configurations.png) + +## How It Works + +1. You **upload** a document (PDF, DOCX, TXT, or JSON) to the Knowledge Base +2. Dograh **processes** and chunks the document for efficient retrieval +3. You **attach** the document to one or more workflow nodes +4. During a call, the agent **searches** the document for relevant information based on the caller's questions and uses it to generate accurate responses + +## Supported File Types + +| Format | Extension | +|--------|-----------| +| PDF | `.pdf` | +| Word | `.docx`, `.doc` | +| Text | `.txt` | +| JSON | `.json` | + +Maximum file size: **5 MB** + +## Uploading Documents + +1. Go to **Knowledge Base Files** in the dashboard +2. Click **Upload New** or drag and drop a file +3. Wait for processing to complete — the document will be chunked and indexed automatically + +## Attaching Documents to Nodes + +Once a document is processed, you can attach it to any **Start Call** or **Agent** node in your workflow: + +1. Open the node edit dialog +2. Scroll to the **Knowledge Base Documents** section +3. Select one or more documents for the agent to reference + +The agent will only search documents attached to the current node, so attach only the documents relevant to that conversation step. + +## Best Practices + +- **Keep documents focused** — a single topic per document produces better retrieval results than a large multi-topic file +- **Use clear, structured content** — headings, lists, and short paragraphs help the chunking process +- **Attach selectively** — only attach documents relevant to a specific node rather than attaching everything everywhere +- **Keep documents up to date** — re-upload when source information changes to avoid stale answers diff --git a/docs/voice-agent/pre-call-data-fetch.mdx b/docs/voice-agent/pre-call-data-fetch.mdx new file mode 100644 index 0000000..aee302b --- /dev/null +++ b/docs/voice-agent/pre-call-data-fetch.mdx @@ -0,0 +1,139 @@ +--- +title: "Pre-Call Data Fetch" +description: "Fetch customer data from your CRM or ERP before the call starts, so your voice agent can greet callers by name and reference their account details." +--- + +Pre-Call Data Fetch allows you to enrich the call context with external data before the voice agent starts speaking. When enabled on the **Start Call** node, Dograh sends an HTTP request to your API as soon as a call is initiated. While the response is loading, the caller hears a ring-back tone. Once the data arrives, it is merged into the call's [initial context](/core-concepts/context-and-variables#initial_context) and becomes available as template variables in your prompts and greetings. + + +## How It Works + +1. A call arrives (inbound) or is initiated (outbound). +2. Dograh sends a **POST** request to your configured endpoint with a standardized payload. +3. The caller hears a ring-back tone while waiting for the response. +4. Your API responds with a JSON object containing `dynamic_variables`. +5. The variables are merged into the call's initial context. +6. The voice agent starts with full access to the fetched data via `{{variable_name}}` syntax. + +## Configuration + +Open the **Start Call** node editor and expand **Advanced Settings**. Toggle **Pre-Call Data Fetch** and configure: + +| Field | Description | +| --- | --- | +| **Endpoint URL** | The URL Dograh will send the POST request to. | +| **Authentication** | Optional credential for authenticating the request. Supports API key, bearer token, basic auth, and custom header. | + +## Request Format + +Dograh sends a `POST` request with the following JSON payload: + +```json +{ + "event": "call_inbound", + "call_inbound": { + "agent_id": 123, + "from_number": "+12137771234", + "to_number": "+12137771235" + } +} +``` + +| Field | Description | +| --- | --- | +| `event` | Always `"call_inbound"`. | +| `call_inbound.agent_id` | The workflow (agent) ID. | +| `call_inbound.from_number` | The caller's phone number (`caller_number` from initial context). | +| `call_inbound.to_number` | The called phone number (`called_number` from initial context). | + +The `Content-Type` header is set to `application/json`. If you configured a credential, the corresponding authentication header is included. + +## Expected Response Format + +Your API should return a **JSON object** with a `2xx` status code. The variables to inject into the call context should be placed inside the `dynamic_variables` key: + +```json +{ + "call_inbound": { + "dynamic_variables": { + "customer_name": "Jane Doe", + "account_status": "active", + "loyalty_tier": "gold", + "open_tickets": 2 + } + } +} +``` + +You can also place `dynamic_variables` at the top level: + +```json +{ + "dynamic_variables": { + "customer_name": "Jane Doe", + "account_status": "active" + } +} +``` + +After the response is received, you can reference these values anywhere template variables are supported: + +- **Greeting**: `Hello {{customer_name}}, thank you for calling!` +- **Prompt**: `The customer is a {{loyalty_tier}} member with {{open_tickets}} open support tickets.` + + +If the response is not a valid JSON object, does not contain `dynamic_variables`, or the request fails or times out, the call proceeds normally without the additional context. The pre-call fetch never blocks or fails a call. + + +## Nested Variables + +If your `dynamic_variables` contain nested objects, you can access them using dot notation: + +```json +{ + "call_inbound": { + "dynamic_variables": { + "customer": { + "name": "Jane Doe", + "address": { + "city": "Los Angeles" + } + } + } + } +} +``` + +Access in prompts as `{{customer.name}}` and `{{customer.address.city}}`. + +## Timeout + +The request has a **10-second timeout**. If your API does not respond within this window, the call proceeds without the fetched data. Design your endpoint to respond as quickly as possible to minimize the ring-back tone duration. + +## Example Integration + +A simple Node.js endpoint that looks up a customer by phone number: + +```javascript +app.post("/dograh/pre-call", async (req, res) => { + const { call_inbound } = req.body; + + const customer = await db.customers.findOne({ + phone: call_inbound.from_number, + }); + + if (!customer) { + return res.json({}); + } + + res.json({ + call_inbound: { + dynamic_variables: { + customer_name: customer.name, + account_status: customer.status, + loyalty_tier: customer.tier, + }, + }, + }); +}); +``` diff --git a/docs/voice-agent/tools/introduction.mdx b/docs/voice-agent/tools/introduction.mdx new file mode 100644 index 0000000..1e10df5 --- /dev/null +++ b/docs/voice-agent/tools/introduction.mdx @@ -0,0 +1,39 @@ +--- +title: "Tools" +description: "Extend your voice agent's capabilities by giving it tools to perform actions during live conversations." +--- + +Tools let your AI agent take actions during a conversation — transfer calls, end calls, or call external APIs — based on the context of the conversation and your prompt instructions. + +When a tool is attached to a workflow node, the LLM decides **when** to invoke it and **what parameters** to pass, based on the user's spoken intent and your node-level instructions. + +## Tool Types + +Dograh provides two categories of tools: + +### Built-in Tools + +Pre-configured tools that handle common telephony operations out of the box: + +- [**Call Transfer**](/voice-agent/tools/call-transfer) — Transfer the active call to a phone number or SIP endpoint +- [**End Call**](/voice-agent/tools/end-call) — Terminate the call when the conversation is complete + +### Custom Tools + +Tools you define to integrate with any external system: + +- [**HTTP API**](/voice-agent/tools/http-api) — Call any REST API endpoint during a conversation (e.g., CRM updates, data lookups, triggering automations) + +## How Tools Work + +1. You **define** a tool with a name, description, and parameters +2. You **attach** the tool to one or more workflow nodes +3. During a call, the LLM reads your node prompt, the tool description, and the caller's intent to decide whether to invoke the tool +4. The tool executes and returns a result that the agent can use to continue the conversation + +## Best Practices + +- **Attach only relevant tools to each node** — fewer tools means more reliable invocations +- **Write clear tool descriptions** — the LLM uses these to decide when to call the tool +- **Guide the LLM in your node prompt** — explicitly describe when a tool should be used +- **Test tool behavior** — verify your agent invokes tools at the right moments using web or phone calls diff --git a/ui/src/components/flow/DocumentSelector.tsx b/ui/src/components/flow/DocumentSelector.tsx index f8de6cf..7b02d93 100644 --- a/ui/src/components/flow/DocumentSelector.tsx +++ b/ui/src/components/flow/DocumentSelector.tsx @@ -1,6 +1,6 @@ "use client"; -import { FileText } from "lucide-react"; +import { ExternalLink, FileText } from "lucide-react"; import Link from "next/link"; import { useMemo } from "react"; @@ -8,6 +8,7 @@ import type { DocumentResponseSchema } from "@/client/types.gen"; import { Button } from "@/components/ui/button"; import { Checkbox } from "@/components/ui/checkbox"; import { Label } from "@/components/ui/label"; +import { KNOWLEDGE_BASE_DOC_URL } from "@/constants/documentation"; interface DocumentSelectorProps { value: string[]; @@ -57,7 +58,10 @@ export const DocumentSelector = ({ <> {description && ( - + )} )} @@ -66,11 +70,12 @@ export const DocumentSelector = ({ No documents available. Upload documents to the knowledge base first.
- - - + +
@@ -83,7 +88,10 @@ export const DocumentSelector = ({ <> {description && ( - + )} )} @@ -123,15 +131,23 @@ export const DocumentSelector = ({ ))} +
+ + + Manage Documents + +
-
- + + {value.length > 0 && ( +

{value.length} {value.length === 1 ? "document" : "documents"} selected - - - Manage Documents - -

+

+ )} ); }; diff --git a/ui/src/components/flow/ToolSelector.tsx b/ui/src/components/flow/ToolSelector.tsx index cf3a100..89c1ed3 100644 --- a/ui/src/components/flow/ToolSelector.tsx +++ b/ui/src/components/flow/ToolSelector.tsx @@ -8,6 +8,7 @@ import type { ToolResponse } from "@/client/types.gen"; import { Button } from "@/components/ui/button"; import { Checkbox } from "@/components/ui/checkbox"; import { Label } from "@/components/ui/label"; +import { TOOLS_INTRODUCTION_DOC_URL } from "@/constants/documentation"; interface ToolSelectorProps { value: string[]; @@ -46,7 +47,8 @@ export function ToolSelector({ {description && ( )} diff --git a/ui/src/components/flow/nodes/StartCall.tsx b/ui/src/components/flow/nodes/StartCall.tsx index ca2949c..9393615 100644 --- a/ui/src/components/flow/nodes/StartCall.tsx +++ b/ui/src/components/flow/nodes/StartCall.tsx @@ -1,5 +1,5 @@ import { NodeProps, NodeToolbar, Position } from "@xyflow/react"; -import { Edit, FileText, Play, PlusIcon, Trash2Icon, Wrench } from "lucide-react"; +import { ChevronRight, Edit, FileText, Play, PlusIcon, Settings, Trash2Icon, Wrench } from "lucide-react"; import { memo, useCallback, useEffect, useMemo, useState } from "react"; import { useWorkflow } from "@/app/workflow/[workflowId]/contexts/WorkflowContext"; @@ -11,12 +11,14 @@ import { MentionTextarea } from "@/components/flow/MentionTextarea"; import { ToolBadges } from "@/components/flow/ToolBadges"; import { ToolSelector } from "@/components/flow/ToolSelector"; import { ExtractionVariable, FlowNodeData } from "@/components/flow/types"; +import { CredentialSelector, UrlInput, validateUrl } from "@/components/http"; import { Button } from "@/components/ui/button"; +import { Collapsible, CollapsibleContent, CollapsibleTrigger } from "@/components/ui/collapsible"; import { Input } from "@/components/ui/input"; import { Label } from "@/components/ui/label"; import { Switch } from "@/components/ui/switch"; import { Textarea } from "@/components/ui/textarea"; -import { CONTEXT_VARIABLES_DOC_URL, NODE_DOCUMENTATION_URLS } from "@/constants/documentation"; +import { CONTEXT_VARIABLES_DOC_URL, NODE_DOCUMENTATION_URLS, PRE_CALL_DATA_FETCH_DOC_URL } from "@/constants/documentation"; import { NodeContent } from "./common/NodeContent"; import { NodeEditDialog } from "./common/NodeEditDialog"; @@ -48,6 +50,12 @@ interface StartCallEditFormProps { setToolUuids: (value: string[]) => void; documentUuids: string[]; setDocumentUuids: (value: string[]) => void; + preCallFetchEnabled: boolean; + setPreCallFetchEnabled: (value: boolean) => void; + preCallFetchUrl: string; + setPreCallFetchUrl: (value: string) => void; + preCallFetchCredentialUuid: string; + setPreCallFetchCredentialUuid: (value: string) => void; tools: ToolResponse[]; documents: DocumentResponseSchema[]; recordings: RecordingResponseSchema[]; @@ -77,6 +85,9 @@ export const StartCall = memo(({ data, selected, id }: StartCallNodeProps) => { const [variables, setVariables] = useState(data.extraction_variables ?? []); const [toolUuids, setToolUuids] = useState(data.tool_uuids ?? []); const [documentUuids, setDocumentUuids] = useState(data.document_uuids ?? []); + const [preCallFetchEnabled, setPreCallFetchEnabled] = useState(data.pre_call_fetch_enabled ?? false); + const [preCallFetchUrl, setPreCallFetchUrl] = useState(data.pre_call_fetch_url ?? ""); + const [preCallFetchCredentialUuid, setPreCallFetchCredentialUuid] = useState(data.pre_call_fetch_credential_uuid ?? ""); // Compute if form has unsaved changes (only check prompt, name, greeting) const isDirty = useMemo(() => { @@ -88,6 +99,14 @@ export const StartCall = memo(({ data, selected, id }: StartCallNodeProps) => { }, [greeting, prompt, name, data]); const handleSave = async () => { + // Validate pre-call fetch URL if enabled + if (preCallFetchEnabled && preCallFetchUrl) { + const urlValidation = validateUrl(preCallFetchUrl); + if (!urlValidation.valid) { + return; + } + } + handleSaveNodeData({ ...data, greeting: greeting || undefined, @@ -102,6 +121,9 @@ export const StartCall = memo(({ data, selected, id }: StartCallNodeProps) => { extraction_variables: variables, tool_uuids: toolUuids.length > 0 ? toolUuids : undefined, document_uuids: documentUuids.length > 0 ? documentUuids : undefined, + pre_call_fetch_enabled: preCallFetchEnabled, + pre_call_fetch_url: preCallFetchEnabled ? preCallFetchUrl || undefined : undefined, + pre_call_fetch_credential_uuid: preCallFetchEnabled && preCallFetchCredentialUuid ? preCallFetchCredentialUuid : undefined, }); setOpen(false); await saveWorkflow(); @@ -122,6 +144,9 @@ export const StartCall = memo(({ data, selected, id }: StartCallNodeProps) => { setVariables(data.extraction_variables ?? []); setToolUuids(data.tool_uuids ?? []); setDocumentUuids(data.document_uuids ?? []); + setPreCallFetchEnabled(data.pre_call_fetch_enabled ?? false); + setPreCallFetchUrl(data.pre_call_fetch_url ?? ""); + setPreCallFetchCredentialUuid(data.pre_call_fetch_credential_uuid ?? ""); } setOpen(newOpen); }; @@ -141,6 +166,9 @@ export const StartCall = memo(({ data, selected, id }: StartCallNodeProps) => { setVariables(data.extraction_variables ?? []); setToolUuids(data.tool_uuids ?? []); setDocumentUuids(data.document_uuids ?? []); + setPreCallFetchEnabled(data.pre_call_fetch_enabled ?? false); + setPreCallFetchUrl(data.pre_call_fetch_url ?? ""); + setPreCallFetchCredentialUuid(data.pre_call_fetch_credential_uuid ?? ""); } }, [data, open]); @@ -243,6 +271,12 @@ export const StartCall = memo(({ data, selected, id }: StartCallNodeProps) => { setToolUuids={setToolUuids} documentUuids={documentUuids} setDocumentUuids={setDocumentUuids} + preCallFetchEnabled={preCallFetchEnabled} + setPreCallFetchEnabled={setPreCallFetchEnabled} + preCallFetchUrl={preCallFetchUrl} + setPreCallFetchUrl={setPreCallFetchUrl} + preCallFetchCredentialUuid={preCallFetchCredentialUuid} + setPreCallFetchCredentialUuid={setPreCallFetchCredentialUuid} tools={tools ?? []} documents={documents ?? []} recordings={recordings ?? []} @@ -278,6 +312,12 @@ const StartCallEditForm = ({ setToolUuids, documentUuids, setDocumentUuids, + preCallFetchEnabled, + setPreCallFetchEnabled, + preCallFetchUrl, + setPreCallFetchUrl, + preCallFetchCredentialUuid, + setPreCallFetchCredentialUuid, tools, documents, recordings, @@ -475,6 +515,57 @@ const StartCallEditForm = ({ description="Select documents from the knowledge base that the agent can reference during this conversation step." /> + + {/* Advanced Settings */} +
+ + + + Advanced Settings + + + + {/* Pre-Call Data Fetch */} +
+ + +
+

+ Fetch data from an external API before the call starts. A standardized POST request with caller/called numbers will be sent. The JSON response fields will be merged into the call context and available as template variables in your prompts.{" "} + Learn more +

+ + {preCallFetchEnabled && ( +
+
+ + + +
+ +
+ + +
+
+ )} + + +
); }; diff --git a/ui/src/components/flow/types.ts b/ui/src/components/flow/types.ts index e268eca..e533277 100644 --- a/ui/src/components/flow/types.ts +++ b/ui/src/components/flow/types.ts @@ -28,6 +28,10 @@ export type FlowNodeData = { detect_voicemail?: boolean; delayed_start?: boolean; delayed_start_duration?: number; + // Pre-call data fetch (StartCall only) + pre_call_fetch_enabled?: boolean; + pre_call_fetch_url?: string; + pre_call_fetch_credential_uuid?: string; // Trigger node specific trigger_path?: string; // Webhook node specific diff --git a/ui/src/constants/documentation.ts b/ui/src/constants/documentation.ts index 7f1ea6a..fd0a1b6 100644 --- a/ui/src/constants/documentation.ts +++ b/ui/src/constants/documentation.ts @@ -12,6 +12,12 @@ export const NODE_DOCUMENTATION_URLS: Record = { export const CONTEXT_VARIABLES_DOC_URL = `${DOCS_BASE}/core-concepts/context-and-variables`; +export const TOOLS_INTRODUCTION_DOC_URL = `${DOCS_BASE}/voice-agent/tools/introduction`; + +export const KNOWLEDGE_BASE_DOC_URL = `${DOCS_BASE}/voice-agent/knowledge-base`; + +export const PRE_CALL_DATA_FETCH_DOC_URL = `${DOCS_BASE}/voice-agent/pre-call-data-fetch`; + export const TOOL_DOCUMENTATION_URLS: Record = { http_api: `${DOCS_BASE}/voice-agent/tools/http-api`, end_call: `${DOCS_BASE}/voice-agent/tools/end-call`,