feat: add Tuner Integration to Dograh (#311)

* Add tuner integration

* bump pipecat version

* chore: update pipecat submodule to match upstream and use tuner-pipecat-sdk 0.2.0

Update pipecat submodule from 0.0.109.dev23 to 13e98d0d9 (the exact commit
upstream dograh-hq/dograh uses after v1.30.1). This installs pipecat-ai as
1.1.0.post277 via setuptools_scm, satisfying tuner-pipecat-sdk 0.2.0's
pipecat-ai>=1.0.0 requirement.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* wire tuner

* feat: refactor integrations into self contained packages

* chore: simplify ensure_public_access_token

* fix: remove NodeSpec and make DTOs the source of truth

* feat: send relevant signal to mcp using to_mcp_dict

* fix: fix tests

* cleanup: remove nango integrations

* feat: add agents.md for integrations

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
This commit is contained in:
Mohamed-Mamdouh 2026-05-20 10:07:33 +01:00 committed by GitHub
parent afa78fe859
commit 5f28c1b2a9
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GPG key ID: B5690EEEBB952194
93 changed files with 3388 additions and 3414 deletions

View file

@ -5,6 +5,7 @@ from loguru import logger
from api.db import db_client
from api.enums import PostHogEvent, WorkflowRunState
from api.services.campaign.circuit_breaker import circuit_breaker
from api.services.integrations import IntegrationRuntimeSession
from api.services.pipecat.audio_config import AudioConfig
from api.services.pipecat.audio_playback import play_audio, play_audio_loop
from api.services.pipecat.in_memory_buffers import (
@ -70,6 +71,7 @@ def register_event_handlers(
pre_call_fetch_task: asyncio.Task | None = None,
fetch_recording_audio=None,
user_provider_id: str | None = None,
integration_runtime_sessions: list[IntegrationRuntimeSession] | None = None,
):
"""Register all event handlers for transport and task events.
@ -319,6 +321,20 @@ def register_event_handlers(
)
# Clean up engine resources (including voicemail detector)
integration_logs: dict[str, object] = {}
for runtime_session in integration_runtime_sessions or []:
try:
session_logs = await runtime_session.on_call_finished(
gathered_context=gathered_context
)
if session_logs:
integration_logs.update(session_logs)
except Exception as e:
logger.error(
f"Error finalizing integration runtime session '{runtime_session.name}': {e}",
exc_info=True,
)
await engine.cleanup()
# ------------------------------------------------------------------
@ -368,14 +384,11 @@ def register_event_handlers(
)
)
# Save real-time feedback logs to workflow run
logs_update: dict[str, object] = {}
if not in_memory_logs_buffer.is_empty:
try:
feedback_events = in_memory_logs_buffer.get_events()
await db_client.update_workflow_run(
run_id=workflow_run_id,
logs={"realtime_feedback_events": feedback_events},
)
logs_update["realtime_feedback_events"] = feedback_events
logger.debug(
f"Saved {len(feedback_events)} feedback events to workflow run logs"
)
@ -384,6 +397,17 @@ def register_event_handlers(
else:
logger.debug("Logs buffer is empty, skipping save")
logs_update.update(integration_logs)
if logs_update:
try:
await db_client.update_workflow_run(
run_id=workflow_run_id,
logs=logs_update,
)
except Exception as e:
logger.error(f"Error saving workflow run logs: {e}", exc_info=True)
# Write buffers to temp files and enqueue combined processing task
audio_temp_path = None
transcript_temp_path = None

View file

@ -7,6 +7,10 @@ from loguru import logger
from api.db import db_client
from api.enums import WorkflowRunMode
from api.services.configuration.registry import ServiceProviders
from api.services.integrations import (
IntegrationRuntimeContext,
create_runtime_sessions,
)
from api.services.pipecat.audio_config import AudioConfig, create_audio_config
from api.services.pipecat.event_handlers import (
register_audio_data_handler,
@ -525,6 +529,18 @@ async def _run_pipeline(
# Create pipeline components
audio_buffer, context = create_pipeline_components(audio_config)
integration_runtime_sessions = create_runtime_sessions(
IntegrationRuntimeContext(
workflow_run_id=workflow_run_id,
workflow_run=workflow_run,
workflow_graph=workflow_graph,
run_definition=run_definition,
user_config=user_config,
is_realtime=is_realtime,
context_messages_provider=lambda: context.messages,
)
)
# Set the context, audio_config, and audio_buffer after creation
engine.set_context(context)
engine.set_audio_config(audio_config)
@ -717,6 +733,14 @@ async def _run_pipeline(
# Create pipeline task with audio configuration
task = create_pipeline_task(pipeline, workflow_run_id, audio_config)
for runtime_session in integration_runtime_sessions:
runtime_session.attach(task)
logger.info(
"[integrations] attached runtime session '{}' for workflow run {}",
runtime_session.name,
workflow_run_id,
)
# Now set the task and transport output on the engine
engine.set_task(task)
engine.set_transport_output(transport.output())
@ -781,6 +805,7 @@ async def _run_pipeline(
pre_call_fetch_task=pre_call_fetch_task,
fetch_recording_audio=fetch_audio,
user_provider_id=user_provider_id,
integration_runtime_sessions=integration_runtime_sessions,
)
register_audio_data_handler(audio_buffer, workflow_run_id, in_memory_audio_buffer)