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feat: add google stt and tts. add folders to organize agents

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Abhishek Kumar 2026-05-22 14:36:50 +05:30
parent 21951eca18
commit ad2fa07058
52 changed files with 3412 additions and 621 deletions
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61
api/alembic/versions/6bd9f67ec994_add_folders_and_workflow_folder_id.py Normal file
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@ -0,0 +1,61 @@
"""add folders and workflow folder_id
Revision ID: 6bd9f67ec994
Revises: 2f638891cbb6
Create Date: 2026-05-22 12:52:30.737380
"""
from typing import Sequence, Union
import sqlalchemy as sa
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "6bd9f67ec994"
down_revision: Union[str, None] = "2f638891cbb6"
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
op.create_table(
"folders",
sa.Column("id", sa.Integer(), nullable=False),
sa.Column("organization_id", sa.Integer(), nullable=False),
sa.Column("name", sa.String(), nullable=False),
sa.Column("created_at", sa.DateTime(timezone=True), nullable=True),
sa.ForeignKeyConstraint(
["organization_id"],
["organizations.id"],
),
sa.PrimaryKeyConstraint("id"),
sa.UniqueConstraint("organization_id", "name", name="uq_folder_org_name"),
)
op.create_index(
op.f("ix_folders_organization_id"), "folders", ["organization_id"], unique=False
)
op.add_column("workflows", sa.Column("folder_id", sa.Integer(), nullable=True))
op.create_index(
op.f("ix_workflows_folder_id"), "workflows", ["folder_id"], unique=False
)
op.create_foreign_key(
"fk_workflows_folder_id",
"workflows",
"folders",
["folder_id"],
["id"],
ondelete="SET NULL",
)
# ### end Alembic commands ###
def downgrade() -> None:
# ### commands auto generated by Alembic - please adjust! ###
op.drop_constraint("fk_workflows_folder_id", "workflows", type_="foreignkey")
op.drop_index(op.f("ix_workflows_folder_id"), table_name="workflows")
op.drop_column("workflows", "folder_id")
op.drop_index(op.f("ix_folders_organization_id"), table_name="folders")
op.drop_table("folders")
# ### end Alembic commands ###

3
api/db/db_client.py
View file

@ -2,6 +2,7 @@ from api.db.agent_trigger_client import AgentTriggerClient
from api.db.api_key_client import APIKeyClient
from api.db.campaign_client import CampaignClient
from api.db.embed_token_client import EmbedTokenClient
from api.db.folder_client import FolderClient
from api.db.integration_client import IntegrationClient
from api.db.knowledge_base_client import KnowledgeBaseClient
from api.db.organization_client import OrganizationClient
@ -41,6 +42,7 @@ class DBClient(
WorkflowRecordingClient,
TelephonyConfigurationClient,
TelephonyPhoneNumberClient,
FolderClient,
):
"""
Unified database client that combines all specialized database operations.
@ -62,6 +64,7 @@ class DBClient(
- WebhookCredentialClient: handles webhook credential operations
- ToolClient: handles tool operations for reusable HTTP API tools
- KnowledgeBaseClient: handles knowledge base document and vector search operations
- FolderClient: handles folder operations for grouping workflows (agents)
"""
pass

115
api/db/folder_client.py Normal file
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@ -0,0 +1,115 @@
from sqlalchemy import func
from sqlalchemy.exc import IntegrityError
from sqlalchemy.future import select
from api.db.base_client import BaseDBClient
from api.db.models import FolderModel, WorkflowModel
from api.enums import WorkflowStatus
class FolderNameConflictError(Exception):
"""Raised when a folder name already exists within the organization."""
class FolderClient(BaseDBClient):
async def create_folder(self, name: str, organization_id: int) -> FolderModel:
async with self.async_session() as session:
folder = FolderModel(name=name, organization_id=organization_id)
session.add(folder)
try:
await session.commit()
except IntegrityError:
await session.rollback()
raise FolderNameConflictError(
f"A folder named '{name}' already exists."
)
await session.refresh(folder)
return folder
async def get_folder(
self, folder_id: int, organization_id: int
) -> FolderModel | None:
"""Fetch a single folder scoped to the organization (tenant isolation)."""
async with self.async_session() as session:
result = await session.execute(
select(FolderModel).where(
FolderModel.id == folder_id,
FolderModel.organization_id == organization_id,
)
)
return result.scalar_one_or_none()
async def list_folders(self, organization_id: int) -> list[FolderModel]:
async with self.async_session() as session:
result = await session.execute(
select(FolderModel)
.where(FolderModel.organization_id == organization_id)
.order_by(FolderModel.name.asc())
)
return result.scalars().all()
async def rename_folder(
self, folder_id: int, name: str, organization_id: int
) -> FolderModel:
async with self.async_session() as session:
result = await session.execute(
select(FolderModel).where(
FolderModel.id == folder_id,
FolderModel.organization_id == organization_id,
)
)
folder = result.scalar_one_or_none()
if folder is None:
raise ValueError(f"Folder with id {folder_id} not found")
folder.name = name
try:
await session.commit()
except IntegrityError:
await session.rollback()
raise FolderNameConflictError(
f"A folder named '{name}' already exists."
)
await session.refresh(folder)
return folder
async def delete_folder(self, folder_id: int, organization_id: int) -> bool:
"""Delete a folder. Member workflows are un-filed (folder_id -> NULL)
via the ON DELETE SET NULL foreign key, never deleted.
"""
async with self.async_session() as session:
result = await session.execute(
select(FolderModel).where(
FolderModel.id == folder_id,
FolderModel.organization_id == organization_id,
)
)
folder = result.scalar_one_or_none()
if folder is None:
return False
await session.delete(folder)
await session.commit()
return True
async def get_active_workflow_counts_by_folder(
self, organization_id: int
) -> dict[int, int]:
"""Return {folder_id: active_workflow_count} for the organization.
Only counts active (non-archived) workflows with a non-NULL folder_id.
"""
async with self.async_session() as session:
result = await session.execute(
select(
WorkflowModel.folder_id,
func.count(WorkflowModel.id).label("count"),
)
.where(
WorkflowModel.organization_id == organization_id,
WorkflowModel.folder_id.is_not(None),
WorkflowModel.status == WorkflowStatus.ACTIVE.value,
)
.group_by(WorkflowModel.folder_id)
)
return {folder_id: count for folder_id, count in result.all()}

35
api/db/models.py
View file

@ -352,6 +352,32 @@ class WorkflowDefinitionModel(Base):
workflow_runs = relationship("WorkflowRunModel", back_populates="definition")
class FolderModel(Base):
"""A folder for grouping workflows (agents) within an organization.
Folders are flat (no nesting) and org-scoped. A workflow belongs to at
most one folder via ``WorkflowModel.folder_id``; a NULL folder_id means
the workflow is "Uncategorized".
"""
__tablename__ = "folders"
id = Column(Integer, primary_key=True, index=True)
organization_id = Column(
Integer, ForeignKey("organizations.id"), nullable=False, index=True
)
organization = relationship("OrganizationModel")
name = Column(String, nullable=False)
created_at = Column(DateTime(timezone=True), default=lambda: datetime.now(UTC))
workflows = relationship("WorkflowModel", back_populates="folder")
# Folder names must be unique within an organization.
__table_args__ = (
UniqueConstraint("organization_id", "name", name="uq_folder_org_name"),
)
class WorkflowModel(Base):
__tablename__ = "workflows"
id = Column(Integer, primary_key=True, index=True)
@ -366,6 +392,15 @@ class WorkflowModel(Base):
user = relationship("UserModel", back_populates="workflows")
organization_id = Column(Integer, ForeignKey("organizations.id"), nullable=True)
organization = relationship("OrganizationModel")
# Optional folder for grouping in the agents list. NULL = "Uncategorized".
# ON DELETE SET NULL: deleting a folder un-files its agents, never deletes them.
folder_id = Column(
Integer,
ForeignKey("folders.id", ondelete="SET NULL"),
nullable=True,
index=True,
)
folder = relationship("FolderModel", back_populates="workflows")
name = Column(String, index=True, nullable=False)
status = Column(
Enum(*[status.value for status in WorkflowStatus], name="workflow_status"),

84
api/db/workflow_client.py
View file

@ -372,6 +372,8 @@ class WorkflowClient(BaseDBClient):
WorkflowModel.name,
WorkflowModel.status,
WorkflowModel.created_at,
WorkflowModel.folder_id,
WorkflowModel.workflow_uuid,
)
)
@ -425,8 +427,26 @@ class WorkflowClient(BaseDBClient):
return result.scalar_one_or_none()
async def get_workflow(
self, workflow_id: int, user_id: int = None, organization_id: int = None
self,
workflow_id: int,
user_id: int | None = None,
organization_id: int | None = None,
) -> WorkflowModel | None:
"""Fetch a workflow by id, scoped to a tenant.
Scoping is mandatory: pass ``organization_id`` (preferred) or
``user_id``. A fully unscoped lookup would let a request-supplied id
reach another tenant's workflow. System/runtime paths that only have a
``workflow_id`` and derive the org from the workflow itself (e.g.
inbound telephony routing) must call ``get_workflow_by_id`` instead —
the explicit unscoped variant.
"""
if user_id is None and organization_id is None:
raise ValueError(
"get_workflow requires organization_id (preferred) or user_id "
"for tenant scoping; use get_workflow_by_id for unscoped "
"system lookups."
)
async with self.async_session() as session:
query = (
select(WorkflowModel)
@ -448,6 +468,13 @@ class WorkflowClient(BaseDBClient):
return result.scalars().first()
async def get_workflow_by_id(self, workflow_id: int) -> WorkflowModel | None:
"""Fetch a workflow by id WITHOUT tenant scoping.
Explicit unscoped variant of ``get_workflow``. Only for system/runtime
contexts that legitimately have just a workflow_id and derive the org
from the workflow itself (e.g. inbound telephony). Never call this with
a request-supplied id on a user-facing path.
"""
async with self.async_session() as session:
result = await session.execute(
select(WorkflowModel)
@ -609,7 +636,7 @@ class WorkflowClient(BaseDBClient):
self,
workflow_id: int,
status: str,
organization_id: int = None,
organization_id: int,
) -> WorkflowModel:
"""
Update the status of a workflow.
@ -617,7 +644,9 @@ class WorkflowClient(BaseDBClient):
Args:
workflow_id: The ID of the workflow to update
status: The new status (active/archived)
organization_id: The organization ID
organization_id: The organization ID. Required and always filtered
on: this is a mutation, so an unscoped query would let a caller
archive another org's workflow (tenant-isolation bypass).
Returns:
The updated WorkflowModel
@ -632,12 +661,12 @@ class WorkflowClient(BaseDBClient):
selectinload(WorkflowModel.current_definition),
selectinload(WorkflowModel.released_definition),
)
.where(WorkflowModel.id == workflow_id)
.where(
WorkflowModel.id == workflow_id,
WorkflowModel.organization_id == organization_id,
)
)
if organization_id:
query = query.where(WorkflowModel.organization_id == organization_id)
result = await session.execute(query)
workflow = result.scalars().first()
@ -654,6 +683,47 @@ class WorkflowClient(BaseDBClient):
await session.refresh(workflow)
return workflow
async def move_workflow_to_folder(
self,
workflow_id: int,
folder_id: int | None,
organization_id: int,
) -> WorkflowModel:
"""Set (or clear) a workflow's folder.
Pass ``folder_id=None`` to move the workflow to "Uncategorized". The
caller must validate that ``folder_id`` belongs to ``organization_id``
before calling (the FK only proves the folder exists, not ownership).
``organization_id`` is required and always filtered on: this is a
mutation, so an unscoped query would let a caller move another org's
workflow (tenant-isolation bypass).
Raises:
ValueError: If the workflow is not found within the organization.
"""
async with self.async_session() as session:
query = select(WorkflowModel).where(
WorkflowModel.id == workflow_id,
WorkflowModel.organization_id == organization_id,
)
result = await session.execute(query)
workflow = result.scalars().first()
if not workflow:
raise ValueError(f"Workflow with ID {workflow_id} not found")
workflow.folder_id = folder_id
try:
await session.commit()
except Exception as e:
await session.rollback()
raise e
await session.refresh(workflow)
return workflow
async def get_workflow_run_count(self, workflow_id: int) -> int:
"""Get the count of runs for a workflow."""
async with self.async_session() as session:

26
api/mcp_server/tools/create_workflow.py
View file

@ -34,6 +34,10 @@ from api.mcp_server.ts_bridge import TsBridgeError, parse_code
from api.services.posthog_client import capture_event
from api.services.workflow.dto import ReactFlowDTO
from api.services.workflow.layout import reconcile_positions
from api.services.workflow.trigger_paths import (
extract_trigger_paths,
validate_trigger_paths,
)
from api.services.workflow.workflow_graph import WorkflowGraph
@ -53,20 +57,6 @@ def _format_errors(errors: list[dict[str, Any]]) -> str:
return "\n".join(parts)
def _extract_trigger_paths(workflow_definition: dict) -> list[str]:
"""Mirror of `routes.workflow.extract_trigger_paths` — kept local so the
MCP layer doesn't depend on the route module."""
if not workflow_definition:
return []
paths: list[str] = []
for node in workflow_definition.get("nodes") or []:
if node.get("type") == "trigger":
trigger_path = (node.get("data") or {}).get("trigger_path")
if trigger_path:
paths.append(trigger_path)
return paths
@traced_tool
async def create_workflow(code: str) -> dict[str, Any]:
"""Parse SDK TypeScript and create a new published workflow.
@ -129,6 +119,12 @@ async def create_workflow(code: str) -> dict[str, Any]:
# 1b. New workflow — no prior version to reconcile against; layout
# places new nodes adjacent to their first incoming neighbor.
payload = reconcile_positions(payload, None)
trigger_path_issues = validate_trigger_paths(payload)
if trigger_path_issues:
return _error_result(
"validation_error",
"\n".join(issue.message for issue in trigger_path_issues),
)
# 2. Pydantic shape check (defence in depth — parser is spec-driven).
try:
@ -144,7 +140,7 @@ async def create_workflow(code: str) -> dict[str, Any]:
# 4. Reject upfront if any trigger path collides with another workflow's
# trigger in this org so we don't leave an orphan workflow record.
trigger_paths = _extract_trigger_paths(payload)
trigger_paths = extract_trigger_paths(payload)
if trigger_paths:
try:
await db_client.assert_trigger_paths_available(

7
api/mcp_server/tools/save_workflow.py
View file

@ -32,6 +32,7 @@ from api.mcp_server.tracing import traced_tool
from api.mcp_server.ts_bridge import TsBridgeError, parse_code
from api.services.workflow.dto import ReactFlowDTO
from api.services.workflow.layout import reconcile_positions
from api.services.workflow.trigger_paths import validate_trigger_paths
from api.services.workflow.workflow_graph import WorkflowGraph
@ -129,6 +130,12 @@ async def save_workflow(workflow_id: int, code: str) -> dict[str, Any]:
# here we fill them back in from what was there before, and pick
# approximate placements for newly-introduced nodes.
payload = reconcile_positions(payload, await _previous_workflow_json(workflow))
trigger_path_issues = validate_trigger_paths(payload)
if trigger_path_issues:
return _error_result(
"validation_error",
"\n".join(issue.message for issue in trigger_path_issues),
)
# 2. Pydantic shape check (defence in depth — parser is spec-driven).
try:

99
api/routes/folder.py Normal file
View file

@ -0,0 +1,99 @@
from datetime import datetime
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, Field, field_validator
from api.db import db_client
from api.db.folder_client import FolderNameConflictError
from api.db.models import UserModel
from api.services.auth.depends import get_user
router = APIRouter(prefix="/folder")
class FolderResponse(BaseModel):
id: int
name: str
created_at: datetime
class CreateFolderRequest(BaseModel):
name: str = Field(..., min_length=1, max_length=100)
@field_validator("name")
@classmethod
def strip_name(cls, v: str) -> str:
v = v.strip()
if not v:
raise ValueError("Folder name cannot be empty")
return v
class UpdateFolderRequest(CreateFolderRequest):
pass
@router.get("/")
async def list_folders(
user: UserModel = Depends(get_user),
) -> list[FolderResponse]:
"""List all folders in the authenticated user's organization."""
folders = await db_client.list_folders(
organization_id=user.selected_organization_id
)
return [
FolderResponse(id=f.id, name=f.name, created_at=f.created_at) for f in folders
]
@router.post("/")
async def create_folder(
request: CreateFolderRequest,
user: UserModel = Depends(get_user),
) -> FolderResponse:
"""Create a new folder in the authenticated user's organization."""
try:
folder = await db_client.create_folder(
name=request.name,
organization_id=user.selected_organization_id,
)
except FolderNameConflictError as e:
raise HTTPException(status_code=409, detail=str(e))
return FolderResponse(id=folder.id, name=folder.name, created_at=folder.created_at)
@router.put("/{folder_id}")
async def rename_folder(
folder_id: int,
request: UpdateFolderRequest,
user: UserModel = Depends(get_user),
) -> FolderResponse:
"""Rename a folder owned by the authenticated user's organization."""
try:
folder = await db_client.rename_folder(
folder_id=folder_id,
name=request.name,
organization_id=user.selected_organization_id,
)
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e))
except FolderNameConflictError as e:
raise HTTPException(status_code=409, detail=str(e))
return FolderResponse(id=folder.id, name=folder.name, created_at=folder.created_at)
@router.delete("/{folder_id}")
async def delete_folder(
folder_id: int,
user: UserModel = Depends(get_user),
) -> dict[str, bool]:
"""Delete a folder. Member agents are moved to "Uncategorized", not deleted."""
deleted = await db_client.delete_folder(
folder_id=folder_id,
organization_id=user.selected_organization_id,
)
if not deleted:
raise HTTPException(
status_code=404, detail=f"Folder with id {folder_id} not found"
)
return {"success": True}

2
api/routes/main.py
View file

@ -6,6 +6,7 @@ from api.routes.agent_stream import router as agent_stream_router
from api.routes.auth import router as auth_router
from api.routes.campaign import router as campaign_router
from api.routes.credentials import router as credentials_router
from api.routes.folder import router as folder_router
from api.routes.knowledge_base import router as knowledge_base_router
from api.routes.node_types import router as node_types_router
from api.routes.organization import router as organization_router
@ -54,6 +55,7 @@ router.include_router(public_download_router)
router.include_router(workflow_embed_router)
router.include_router(knowledge_base_router)
router.include_router(workflow_recording_router)
router.include_router(folder_router)
router.include_router(auth_router)
router.include_router(node_types_router)
router.include_router(agent_stream_router)

294
api/routes/public_agent.py
View file

@ -1,18 +1,19 @@
"""Public API endpoints for agent triggers.
"""Public API endpoints for public agent execution.
These endpoints are accessible with API key authentication and allow
external systems to programmatically trigger phone calls.
"""
import random
from typing import Optional
from dataclasses import dataclass
from typing import Awaitable, Callable, Optional
from fastapi import APIRouter, Header, HTTPException
from loguru import logger
from pydantic import BaseModel
from api.db import db_client
from api.enums import TriggerState
from api.enums import TriggerState, WorkflowStatus
from api.services.quota_service import check_dograh_quota_by_user_id
from api.services.telephony.factory import (
get_default_telephony_provider,
@ -39,6 +40,14 @@ class TriggerCallResponse(BaseModel):
workflow_run_name: str
@dataclass
class ResolvedAgentTarget:
workflow: object
organization_id: int
identifier_type: str
identifier_value: str
def trigger_exists_in_workflow(workflow_definition: dict, trigger_path: str) -> bool:
"""Check if trigger node exists in workflow definition.
@ -57,72 +66,133 @@ def trigger_exists_in_workflow(workflow_definition: dict, trigger_path: str) ->
return False
async def _initiate_call(
uuid: str,
request: TriggerCallRequest,
x_api_key: str,
*,
use_draft: bool,
) -> TriggerCallResponse:
"""Shared core for production and test trigger endpoints.
When ``use_draft`` is True the latest draft definition is executed;
otherwise the published (released) definition is used.
"""
# 1. Validate API key
async def _validate_api_key(x_api_key: str):
"""Validate the org API key used to invoke a public agent endpoint."""
api_key = await db_client.validate_api_key(x_api_key)
if not api_key:
raise HTTPException(status_code=401, detail="Invalid API key")
return api_key
# 2. Lookup agent trigger by UUID
trigger = await db_client.get_agent_trigger_by_path(uuid)
def _ensure_workflow_is_active(workflow) -> None:
if workflow.status != WorkflowStatus.ACTIVE.value:
raise HTTPException(status_code=404, detail="Workflow is not active")
def _get_execution_user_id(workflow) -> int:
if workflow.user_id is None:
raise HTTPException(
status_code=409,
detail="Workflow has no execution owner",
)
return workflow.user_id
async def _get_workflow_definition_for_execution(workflow, *, use_draft: bool) -> dict:
"""Return the definition that would execute for this public agent request."""
if use_draft:
draft = await db_client.get_draft_version(workflow.id)
if draft:
return draft.workflow_json
if workflow.released_definition is None:
raise HTTPException(
status_code=404, detail="Workflow has no published definition"
)
return workflow.released_definition.workflow_json
async def _resolve_trigger_target(
trigger_path: str,
organization_id: int,
*,
use_draft: bool,
) -> ResolvedAgentTarget:
"""Resolve a trigger UUID to a workflow, scoped to the API key's org."""
trigger = await db_client.get_agent_trigger_by_path(trigger_path)
if not trigger:
raise HTTPException(status_code=404, detail="Agent trigger not found")
# 3. Validate organization match (API key org must match trigger org)
if api_key.organization_id != trigger.organization_id:
if organization_id != trigger.organization_id:
raise HTTPException(status_code=403, detail="Access denied")
# 4. Validate trigger is active
if trigger.state != TriggerState.ACTIVE.value:
raise HTTPException(status_code=404, detail="Agent trigger is not active")
# 4.5 Check Dograh quota before initiating the call (apply the trigger's
# workflow's model_overrides so we evaluate the keys this run will use).
workflow = await db_client.get_workflow(
trigger.workflow_id,
organization_id=organization_id,
)
if not workflow:
raise HTTPException(status_code=404, detail="Workflow not found")
_ensure_workflow_is_active(workflow)
workflow_definition = await _get_workflow_definition_for_execution(
workflow,
use_draft=use_draft,
)
if not trigger_exists_in_workflow(workflow_definition, trigger_path):
raise HTTPException(
status_code=404,
detail="Trigger not found in the selected Agent",
)
return ResolvedAgentTarget(
workflow=workflow,
organization_id=organization_id,
identifier_type="trigger_path",
identifier_value=trigger_path,
)
async def _resolve_workflow_uuid_target(
workflow_uuid: str,
organization_id: int,
*,
use_draft: bool,
) -> ResolvedAgentTarget:
"""Resolve a workflow UUID directly, scoped to the API key's org."""
workflow = await db_client.get_workflow_by_uuid(workflow_uuid, organization_id)
if not workflow:
raise HTTPException(status_code=404, detail="Workflow not found")
_ensure_workflow_is_active(workflow)
await _get_workflow_definition_for_execution(workflow, use_draft=use_draft)
return ResolvedAgentTarget(
workflow=workflow,
organization_id=organization_id,
identifier_type="workflow_uuid",
identifier_value=workflow_uuid,
)
async def _execute_resolved_target(
target: ResolvedAgentTarget,
request: TriggerCallRequest,
*,
use_draft: bool,
api_key_id: int | None,
api_key_created_by: int | None,
) -> TriggerCallResponse:
"""Shared execution path once the target workflow has been resolved."""
execution_user_id = _get_execution_user_id(target.workflow)
# Check Dograh quota using the workflow owner's config and model overrides.
quota_result = await check_dograh_quota_by_user_id(
api_key.created_by, workflow_id=trigger.workflow_id
execution_user_id,
workflow_id=target.workflow.id,
)
if not quota_result.has_quota:
raise HTTPException(status_code=402, detail=quota_result.error_message)
# 5. Get workflow and resolve the definition (published vs draft)
workflow = await db_client.get_workflow_by_id(trigger.workflow_id)
if not workflow:
raise HTTPException(status_code=404, detail="Workflow not found")
if use_draft:
draft = await db_client.get_draft_version(trigger.workflow_id)
# Fall back to the published definition when no draft exists, so the
# test URL always runs *something* — typically the same agent the
# production URL would run.
workflow_definition = (
draft.workflow_json if draft else workflow.released_definition.workflow_json
)
else:
workflow_definition = workflow.released_definition.workflow_json
# Validate trigger node still exists in the resolved definition
if not trigger_exists_in_workflow(workflow_definition, uuid):
raise HTTPException(
status_code=404,
detail="Trigger not found in the published Agent",
)
# 6. Get telephony provider — either the caller-specified config (validated
# against the trigger's org) or the org's default config.
# Get telephony provider — either the caller-specified config (validated
# against the workflow's org) or the org's default config.
if request.telephony_configuration_id is not None:
cfg = await db_client.get_telephony_configuration_for_org(
request.telephony_configuration_id, trigger.organization_id
request.telephony_configuration_id,
target.organization_id,
)
if not cfg:
raise HTTPException(
@ -130,7 +200,7 @@ async def _initiate_call(
)
try:
provider = await get_telephony_provider_by_id(
cfg.id, trigger.organization_id
cfg.id, target.organization_id
)
except ValueError:
raise HTTPException(
@ -140,14 +210,14 @@ async def _initiate_call(
resolved_cfg_id = cfg.id
else:
try:
provider = await get_default_telephony_provider(trigger.organization_id)
provider = await get_default_telephony_provider(target.organization_id)
except ValueError:
raise HTTPException(
status_code=400,
detail="Telephony provider not configured for this organization",
)
default_cfg = await db_client.get_default_telephony_configuration(
trigger.organization_id
target.organization_id
)
resolved_cfg_id = default_cfg.id if default_cfg else None
@ -164,24 +234,36 @@ async def _initiate_call(
# 8. Create workflow run
mode_label = "TEST" if use_draft else "API"
workflow_run_name = f"WR-{mode_label}-{random.randint(1000, 9999)}"
initial_context = {
"provider": provider.PROVIDER_NAME,
"phone_number": request.phone_number,
"trigger_mode": "test" if use_draft else "production",
"telephony_configuration_id": resolved_cfg_id,
"agent_identifier": target.identifier_value,
"agent_identifier_type": target.identifier_type,
"workflow_uuid": target.workflow.workflow_uuid,
}
if target.identifier_type == "trigger_path":
initial_context["agent_uuid"] = target.identifier_value
if api_key_id is not None:
initial_context["api_key_id"] = api_key_id
if api_key_created_by is not None:
initial_context["api_key_created_by"] = api_key_created_by
initial_context.update(request.initial_context or {})
workflow_run = await db_client.create_workflow_run(
name=workflow_run_name,
workflow_id=trigger.workflow_id,
workflow_id=target.workflow.id,
mode=workflow_run_mode,
initial_context={
"provider": provider.PROVIDER_NAME,
"phone_number": request.phone_number,
"agent_uuid": uuid,
"trigger_mode": "test" if use_draft else "production",
"telephony_configuration_id": resolved_cfg_id,
**(request.initial_context or {}),
},
user_id=api_key.created_by,
initial_context=initial_context,
user_id=execution_user_id,
use_draft=use_draft,
organization_id=target.organization_id,
)
logger.info(
f"Created workflow run {workflow_run.id} for API trigger {uuid} "
f"Created workflow run {workflow_run.id} for public agent "
f"{target.identifier_type}={target.identifier_value} "
f"(mode={'test' if use_draft else 'production'}) "
f"to phone number {request.phone_number}"
)
@ -192,10 +274,10 @@ async def _initiate_call(
webhook_url = (
f"{backend_endpoint}/api/v1/telephony/{webhook_endpoint}"
f"?workflow_id={trigger.workflow_id}"
f"&user_id={api_key.created_by}"
f"?workflow_id={target.workflow.id}"
f"&user_id={execution_user_id}"
f"&workflow_run_id={workflow_run.id}"
f"&organization_id={trigger.organization_id}"
f"&organization_id={target.organization_id}"
)
# 10. Initiate call via telephony provider. workflow_id and user_id are
@ -207,8 +289,8 @@ async def _initiate_call(
to_number=request.phone_number,
webhook_url=webhook_url,
workflow_run_id=workflow_run.id,
workflow_id=trigger.workflow_id,
user_id=api_key.created_by,
workflow_id=target.workflow.id,
user_id=execution_user_id,
)
except Exception as e:
logger.warning(
@ -221,7 +303,7 @@ async def _initiate_call(
logger.info(
f"Call initiated successfully for workflow run {workflow_run.id} "
f"via trigger {uuid}"
f"via {target.identifier_type}={target.identifier_value}"
)
return TriggerCallResponse(
@ -231,6 +313,30 @@ async def _initiate_call(
)
async def _initiate_call(
identifier: str,
request: TriggerCallRequest,
x_api_key: str,
*,
use_draft: bool,
target_resolver: Callable[..., Awaitable[ResolvedAgentTarget]],
) -> TriggerCallResponse:
"""Resolve the requested public target, then execute the common call flow."""
api_key = await _validate_api_key(x_api_key)
target = await target_resolver(
identifier,
api_key.organization_id,
use_draft=use_draft,
)
return await _execute_resolved_target(
target,
request,
use_draft=use_draft,
api_key_id=api_key.id,
api_key_created_by=api_key.created_by,
)
@router.post("/{uuid}", response_model=TriggerCallResponse)
async def initiate_call(
uuid: str,
@ -241,7 +347,13 @@ async def initiate_call(
Executes the workflow's currently released definition.
"""
return await _initiate_call(uuid, request, x_api_key, use_draft=False)
return await _initiate_call(
uuid,
request,
x_api_key,
use_draft=False,
target_resolver=_resolve_trigger_target,
)
@router.post("/test/{uuid}", response_model=TriggerCallResponse)
@ -255,4 +367,42 @@ async def initiate_call_test(
Useful for verifying changes before publishing. Falls back to the
published definition when no draft exists.
"""
return await _initiate_call(uuid, request, x_api_key, use_draft=True)
return await _initiate_call(
uuid,
request,
x_api_key,
use_draft=True,
target_resolver=_resolve_trigger_target,
)
@router.post("/workflow/{workflow_uuid}", response_model=TriggerCallResponse)
async def initiate_call_by_workflow_uuid(
workflow_uuid: str,
request: TriggerCallRequest,
x_api_key: str = Header(..., alias="X-API-Key"),
):
"""Initiate a phone call against the published workflow identified by UUID."""
return await _initiate_call(
workflow_uuid,
request,
x_api_key,
use_draft=False,
target_resolver=_resolve_workflow_uuid_target,
)
@router.post("/test/workflow/{workflow_uuid}", response_model=TriggerCallResponse)
async def initiate_call_test_by_workflow_uuid(
workflow_uuid: str,
request: TriggerCallRequest,
x_api_key: str = Header(..., alias="X-API-Key"),
):
"""Initiate a phone call against the latest draft of the workflow by UUID."""
return await _initiate_call(
workflow_uuid,
request,
x_api_key,
use_draft=True,
target_resolver=_resolve_workflow_uuid_target,
)

9
api/routes/telephony.py
View file

@ -305,7 +305,9 @@ async def _validate_inbound_request(
"""
from api.services.telephony import registry as telephony_registry
workflow = await db_client.get_workflow(workflow_id)
# System lookup: inbound routing only has the workflow_id and derives the
# org/user from the workflow itself, so use the explicit unscoped variant.
workflow = await db_client.get_workflow_by_id(workflow_id)
if not workflow:
return False, TelephonyError.WORKFLOW_NOT_FOUND, {}, None
@ -528,8 +530,9 @@ async def _handle_telephony_websocket(
await websocket.close(code=4404, reason="Workflow run not found")
return
# Get workflow for organization info
workflow = await db_client.get_workflow(workflow_id)
# Get workflow for organization info. System lookup keyed only on the
# workflow_id (org is derived below) — use the explicit unscoped variant.
workflow = await db_client.get_workflow_by_id(workflow_id)
if not workflow:
logger.error(f"Workflow {workflow_id} not found")
await websocket.close(code=4404, reason="Workflow not found")

190
api/routes/workflow.py
View file

@ -32,99 +32,16 @@ from api.services.storage import storage_fs
from api.services.workflow.dto import ReactFlowDTO, sanitize_workflow_definition
from api.services.workflow.duplicate import duplicate_workflow
from api.services.workflow.errors import ItemKind, WorkflowError
from api.services.workflow.trigger_paths import (
TriggerPathIssue,
ensure_trigger_paths,
extract_trigger_paths,
regenerate_trigger_uuids,
trigger_path_to_node_id,
validate_trigger_paths,
)
from api.services.workflow.workflow_graph import WorkflowGraph
def extract_trigger_paths(workflow_definition: dict) -> List[str]:
"""Extract trigger UUIDs from workflow definition.
Args:
workflow_definition: The workflow definition JSON
Returns:
List of trigger UUIDs found in the workflow
"""
if not workflow_definition:
return []
nodes = workflow_definition.get("nodes", [])
trigger_paths = []
for node in nodes:
if node.get("type") == "trigger":
trigger_path = node.get("data", {}).get("trigger_path")
if trigger_path:
trigger_paths.append(trigger_path)
return trigger_paths
def _trigger_path_to_node_id(workflow_definition: dict) -> dict[str, str]:
"""Map each trigger node's trigger_path to its node id."""
if not workflow_definition:
return {}
out: dict[str, str] = {}
for node in workflow_definition.get("nodes", []):
if node.get("type") == "trigger":
tp = node.get("data", {}).get("trigger_path")
if tp:
out[tp] = node.get("id")
return out
def regenerate_trigger_uuids(workflow_definition: dict) -> dict:
"""Regenerate UUIDs for all trigger nodes in a workflow definition.
This should be called when creating a new workflow from a template or
duplicating a workflow to avoid trigger UUID conflicts.
Args:
workflow_definition: The workflow definition JSON
Returns:
Updated workflow definition with new trigger UUIDs
"""
if not workflow_definition:
return workflow_definition
# Deep copy to avoid modifying the original
import copy
updated_definition = copy.deepcopy(workflow_definition)
nodes = updated_definition.get("nodes", [])
for node in nodes:
if node.get("type") == "trigger":
# Generate a new UUID for this trigger
if "data" not in node:
node["data"] = {}
node["data"]["trigger_path"] = str(uuid.uuid4())
return updated_definition
def ensure_trigger_paths(workflow_definition: Optional[dict]) -> Optional[dict]:
"""Mint a UUID for any trigger node that's missing ``data.trigger_path``.
Trigger nodes that already carry a non-empty trigger_path are left
untouched so stable IDs survive edits. The input is not mutated; the
returned dict is what should be persisted and echoed in the response.
"""
if not workflow_definition:
return workflow_definition
import copy
out = copy.deepcopy(workflow_definition)
for node in out.get("nodes") or []:
if node.get("type") != "trigger":
continue
data = node.setdefault("data", {})
if not data.get("trigger_path"):
data["trigger_path"] = str(uuid.uuid4())
return out
router = APIRouter(prefix="/workflow")
@ -139,7 +56,7 @@ def _trigger_conflict_http_exception(
"""Build a 409 with the same detail shape as validate's 422 so the editor
can highlight the offending trigger node(s) using the same code path."""
path_to_node = (
_trigger_path_to_node_id(workflow_definition) if workflow_definition else {}
trigger_path_to_node_id(workflow_definition) if workflow_definition else {}
)
errors: list[WorkflowError] = [
WorkflowError(
@ -159,6 +76,24 @@ def _trigger_conflict_http_exception(
)
def _trigger_path_validation_http_exception(
issues: list[TriggerPathIssue],
) -> HTTPException:
errors = [
WorkflowError(
kind=ItemKind.node,
id=issue.node_id,
field="data.trigger_path",
message=issue.message,
)
for issue in issues
]
return HTTPException(
status_code=422,
detail=ValidateWorkflowResponse(is_valid=False, errors=errors).model_dump(),
)
async def _validate_workflow_definition(
workflow_definition: Optional[dict],
exclude_workflow_id: Optional[int] = None,
@ -187,6 +122,17 @@ async def _validate_workflow_definition(
except ValueError as e:
errors.extend(e.args[0])
# ----------- Trigger Path Format Check ------------
for issue in validate_trigger_paths(workflow_definition):
errors.append(
WorkflowError(
kind=ItemKind.node,
id=issue.node_id,
field="data.trigger_path",
message=issue.message,
)
)
# ----------- Trigger Path Conflict Check ------------
trigger_paths = extract_trigger_paths(workflow_definition)
if trigger_paths:
@ -195,7 +141,7 @@ async def _validate_workflow_definition(
exclude_workflow_id=exclude_workflow_id,
)
if conflicts:
path_to_node = _trigger_path_to_node_id(workflow_definition)
path_to_node = trigger_path_to_node_id(workflow_definition)
for conflicting_path in conflicts:
errors.append(
WorkflowError(
@ -251,6 +197,14 @@ class WorkflowListResponse(BaseModel):
status: str
created_at: datetime
total_runs: int
folder_id: int | None = None
workflow_uuid: str | None = None
class MoveWorkflowToFolderRequest(BaseModel):
"""Move a workflow into a folder, or to "Uncategorized" when null."""
folder_id: int | None = None
class WorkflowCountResponse(BaseModel):
@ -404,6 +358,9 @@ async def create_workflow(
# Auto-mint trigger_path for any trigger node that didn't ship one so
# clients don't need to generate UUIDs themselves.
workflow_definition = ensure_trigger_paths(request.workflow_definition)
trigger_path_issues = validate_trigger_paths(workflow_definition)
if trigger_path_issues:
raise _trigger_path_validation_http_exception(trigger_path_issues)
# Validate trigger path uniqueness BEFORE creating the workflow so we
# don't leave an orphaned workflow record when the trigger conflicts.
@ -641,6 +598,8 @@ async def get_workflows(
status=workflow.status,
created_at=workflow.created_at,
total_runs=run_counts.get(workflow.id, 0),
folder_id=workflow.folder_id,
workflow_uuid=workflow.workflow_uuid,
)
for workflow in workflows
]
@ -883,6 +842,48 @@ async def update_workflow_status(
raise HTTPException(status_code=500, detail=str(e))
@router.put("/{workflow_id}/folder")
async def move_workflow_to_folder(
workflow_id: int,
request: MoveWorkflowToFolderRequest,
user: UserModel = Depends(get_user),
) -> WorkflowListResponse:
"""Move a workflow into a folder, or to "Uncategorized" (folder_id=null).
Validates that the target folder belongs to the caller's organization —
the FK alone proves the folder exists, not that the caller may use it.
"""
# Validate target folder ownership (tenant isolation) unless un-filing.
if request.folder_id is not None:
folder = await db_client.get_folder(
request.folder_id, organization_id=user.selected_organization_id
)
if folder is None:
raise HTTPException(
status_code=404,
detail=f"Folder with id {request.folder_id} not found",
)
try:
workflow = await db_client.move_workflow_to_folder(
workflow_id=workflow_id,
folder_id=request.folder_id,
organization_id=user.selected_organization_id,
)
except ValueError as e:
raise HTTPException(status_code=404, detail=str(e))
run_count = await db_client.get_workflow_run_count(workflow.id)
return WorkflowListResponse(
id=workflow.id,
name=workflow.name,
status=workflow.status,
created_at=workflow.created_at,
total_runs=run_count,
folder_id=workflow.folder_id,
)
@router.put(
"/{workflow_id}",
**sdk_expose(
@ -917,6 +918,9 @@ async def update_workflow(
# response echoes workflow_definition so the client picks up the new
# UUID without a refetch.
workflow_definition = ensure_trigger_paths(workflow_definition)
trigger_path_issues = validate_trigger_paths(workflow_definition)
if trigger_path_issues:
raise _trigger_path_validation_http_exception(trigger_path_issues)
if workflow_definition:
existing_workflow = await db_client.get_workflow(
workflow_id, organization_id=user.selected_organization_id

49
api/services/configuration/options/__init__.py Normal file
View file

@ -0,0 +1,49 @@
from .deepgram import DEEPGRAM_LANGUAGES, DEEPGRAM_STT_MODELS
from .gladia import GLADIA_STT_LANGUAGES, GLADIA_STT_MODELS
from .google import (
GOOGLE_MODELS,
GOOGLE_REALTIME_LANGUAGES,
GOOGLE_REALTIME_MODELS,
GOOGLE_REALTIME_VOICES,
GOOGLE_STT_LANGUAGES,
GOOGLE_STT_MODELS,
GOOGLE_TTS_LANGUAGES,
GOOGLE_TTS_MODELS,
GOOGLE_TTS_VOICES,
GOOGLE_VERTEX_REALTIME_LANGUAGES,
GOOGLE_VERTEX_REALTIME_MODELS,
GOOGLE_VERTEX_REALTIME_VOICES,
)
from .sarvam import (
SARVAM_LANGUAGES,
SARVAM_STT_MODELS,
SARVAM_TTS_MODELS,
SARVAM_V2_VOICES,
SARVAM_V3_VOICES,
)
from .speechmatics import SPEECHMATICS_STT_LANGUAGES
__all__ = [
"DEEPGRAM_LANGUAGES",
"DEEPGRAM_STT_MODELS",
"GLADIA_STT_LANGUAGES",
"GLADIA_STT_MODELS",
"GOOGLE_MODELS",
"GOOGLE_REALTIME_LANGUAGES",
"GOOGLE_REALTIME_MODELS",
"GOOGLE_REALTIME_VOICES",
"GOOGLE_STT_LANGUAGES",
"GOOGLE_STT_MODELS",
"GOOGLE_TTS_LANGUAGES",
"GOOGLE_TTS_MODELS",
"GOOGLE_TTS_VOICES",
"GOOGLE_VERTEX_REALTIME_LANGUAGES",
"GOOGLE_VERTEX_REALTIME_MODELS",
"GOOGLE_VERTEX_REALTIME_VOICES",
"SARVAM_LANGUAGES",
"SARVAM_STT_MODELS",
"SARVAM_TTS_MODELS",
"SARVAM_V2_VOICES",
"SARVAM_V3_VOICES",
"SPEECHMATICS_STT_LANGUAGES",
]

84
api/services/configuration/options/deepgram.py Normal file
View file

@ -0,0 +1,84 @@
DEEPGRAM_STT_MODELS = ("nova-3-general", "flux-general-en", "flux-general-multi")
DEEPGRAM_LANGUAGES = (
"multi",
"ar",
"ar-AE",
"ar-SA",
"ar-QA",
"ar-KW",
"ar-SY",
"ar-LB",
"ar-PS",
"ar-JO",
"ar-EG",
"ar-SD",
"ar-TD",
"ar-MA",
"ar-DZ",
"ar-TN",
"ar-IQ",
"ar-IR",
"be",
"bn",
"bs",
"bg",
"ca",
"cs",
"da",
"da-DK",
"de",
"de-CH",
"el",
"en",
"en-US",
"en-AU",
"en-GB",
"en-IN",
"en-NZ",
"es",
"es-419",
"et",
"fa",
"fi",
"fr",
"fr-CA",
"he",
"hi",
"hr",
"hu",
"id",
"it",
"ja",
"kn",
"ko",
"ko-KR",
"lt",
"lv",
"mk",
"mr",
"ms",
"nl",
"nl-BE",
"no",
"pl",
"pt",
"pt-BR",
"pt-PT",
"ro",
"ru",
"sk",
"sl",
"sr",
"sv",
"sv-SE",
"ta",
"te",
"th",
"tl",
"tr",
"uk",
"ur",
"vi",
"zh-CN",
"zh-TW",
)

103
api/services/configuration/options/gladia.py Normal file
View file

@ -0,0 +1,103 @@
GLADIA_STT_MODELS = ("solaria-1",)
GLADIA_STT_LANGUAGES = (
"af",
"am",
"ar",
"as",
"az",
"ba",
"be",
"bg",
"bn",
"bo",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"eu",
"fa",
"fi",
"fo",
"fr",
"gl",
"gu",
"ha",
"haw",
"he",
"hi",
"hr",
"ht",
"hu",
"hy",
"id",
"is",
"it",
"ja",
"jw",
"ka",
"kk",
"km",
"kn",
"ko",
"la",
"lb",
"ln",
"lo",
"lt",
"lv",
"mg",
"mi",
"mk",
"ml",
"mn",
"mr",
"ms",
"mt",
"my",
"ne",
"nl",
"nn",
"no",
"oc",
"pa",
"pl",
"ps",
"pt",
"ro",
"ru",
"sa",
"sd",
"si",
"sk",
"sl",
"sn",
"so",
"sq",
"sr",
"su",
"sv",
"sw",
"ta",
"te",
"tg",
"th",
"tk",
"tl",
"tr",
"tt",
"uk",
"ur",
"uz",
"vi",
"wo",
"yi",
"yo",
"zh",
)

273
api/services/configuration/options/google.py Normal file
View file

@ -0,0 +1,273 @@
GOOGLE_MODELS = (
"gemini-2.0-flash",
"gemini-2.0-flash-lite",
"gemini-2.5-flash",
"gemini-2.5-flash-lite",
)
GOOGLE_REALTIME_MODELS = ("gemini-3.1-flash-live-preview",)
GOOGLE_REALTIME_VOICES = ("Puck", "Charon", "Kore", "Fenrir", "Aoede")
GOOGLE_REALTIME_LANGUAGES = (
"ar",
"bn",
"de",
"en",
"es",
"fr",
"gu",
"hi",
"id",
"it",
"ja",
"kn",
"ko",
"ml",
"mr",
"nl",
"pl",
"pt",
"ru",
"ta",
"te",
"th",
"tr",
"vi",
"zh",
)
GOOGLE_VERTEX_REALTIME_MODELS = ("google/gemini-live-2.5-flash-native-audio",)
GOOGLE_VERTEX_REALTIME_VOICES = GOOGLE_REALTIME_VOICES
GOOGLE_VERTEX_REALTIME_LANGUAGES = GOOGLE_REALTIME_LANGUAGES
GOOGLE_STT_MODELS = ("latest_long", "latest_short", "chirp_3")
# Docs-derived from Google Cloud Speech-to-Text V2 supported languages.
GOOGLE_STT_LANGUAGES = (
"af-ZA",
"am-ET",
"ar-AE",
"ar-BH",
"ar-DZ",
"ar-EG",
"ar-IL",
"ar-IQ",
"ar-JO",
"ar-KW",
"ar-LB",
"ar-MA",
"ar-MR",
"ar-OM",
"ar-PS",
"ar-QA",
"ar-SA",
"ar-SY",
"ar-TN",
"ar-XA",
"ar-YE",
"as-IN",
"ast-ES",
"az-AZ",
"be-BY",
"bg-BG",
"bn-BD",
"bn-IN",
"bs-BA",
"ca-ES",
"ceb-PH",
"ckb-IQ",
"cmn-Hans-CN",
"cmn-Hant-TW",
"cs-CZ",
"cy-GB",
"da-DK",
"de-AT",
"de-CH",
"de-DE",
"el-GR",
"en-AU",
"en-GB",
"en-HK",
"en-IE",
"en-IN",
"en-NZ",
"en-PH",
"en-PK",
"en-SG",
"en-US",
"es-419",
"es-AR",
"es-BO",
"es-CL",
"es-CO",
"es-CR",
"es-DO",
"es-EC",
"es-ES",
"es-GT",
"es-HN",
"es-MX",
"es-NI",
"es-PA",
"es-PE",
"es-PR",
"es-SV",
"es-US",
"es-UY",
"es-VE",
"et-EE",
"eu-ES",
"fa-IR",
"ff-SN",
"fi-FI",
"fil-PH",
"fr-BE",
"fr-CA",
"fr-CH",
"fr-FR",
"ga-IE",
"gl-ES",
"gu-IN",
"ha-NG",
"hi-IN",
"hr-HR",
"hu-HU",
"hy-AM",
"id-ID",
"ig-NG",
"is-IS",
"it-CH",
"it-IT",
"iw-IL",
"ja-JP",
"jv-ID",
"ka-GE",
"kam-KE",
"kea-CV",
"kk-KZ",
"km-KH",
"kn-IN",
"ko-KR",
"ky-KG",
"lb-LU",
"lg-UG",
"ln-CD",
"lo-LA",
"lt-LT",
"luo-KE",
"lv-LV",
"mi-NZ",
"mk-MK",
"ml-IN",
"mn-MN",
"mr-IN",
"ms-MY",
"mt-MT",
"my-MM",
"ne-NP",
"nl-BE",
"nl-NL",
"no-NO",
"nso-ZA",
"ny-MW",
"oc-FR",
"om-ET",
"or-IN",
"pa-Guru-IN",
"pl-PL",
"ps-AF",
"pt-BR",
"pt-PT",
"ro-RO",
"ru-RU",
"rup-BG",
"rw-RW",
"sd-IN",
"si-LK",
"sk-SK",
"sl-SI",
"sn-ZW",
"so-SO",
"sq-AL",
"sr-RS",
"ss-Latn-ZA",
"st-ZA",
"su-ID",
"sv-SE",
"sw",
"sw-KE",
"ta-IN",
"te-IN",
"tg-TJ",
"th-TH",
"tn-Latn-ZA",
"tr-TR",
"ts-ZA",
"uk-UA",
"umb-AO",
"ur-PK",
"uz-UZ",
"ve-ZA",
"vi-VN",
"wo-SN",
"xh-ZA",
"yo-NG",
"yue-Hant-HK",
"zu-ZA",
)
GOOGLE_TTS_MODELS = ("chirp_3_hd",)
GOOGLE_TTS_VOICES = ("en-US-Chirp3-HD-Charon",)
GOOGLE_TTS_LANGUAGES = (
"ar-XA",
"bn-IN",
"bg-BG",
"yue-HK",
"hr-HR",
"cs-CZ",
"da-DK",
"nl-BE",
"nl-NL",
"en-AU",
"en-IN",
"en-GB",
"en-US",
"et-EE",
"fi-FI",
"fr-CA",
"fr-FR",
"de-DE",
"el-GR",
"gu-IN",
"he-IL",
"hi-IN",
"hu-HU",
"id-ID",
"it-IT",
"ja-JP",
"kn-IN",
"ko-KR",
"lv-LV",
"lt-LT",
"ml-IN",
"cmn-CN",
"mr-IN",
"nb-NO",
"pl-PL",
"pt-BR",
"pa-IN",
"ro-RO",
"ru-RU",
"sr-RS",
"sk-SK",
"sl-SI",
"es-ES",
"es-US",
"sw-KE",
"sv-SE",
"ta-IN",
"te-IN",
"th-TH",
"tr-TR",
"uk-UA",
"ur-IN",
"vi-VN",
)

66
api/services/configuration/options/sarvam.py Normal file
View file

@ -0,0 +1,66 @@
SARVAM_TTS_MODELS = ("bulbul:v2", "bulbul:v3")
SARVAM_V2_VOICES = (
"anushka",
"manisha",
"vidya",
"arya",
"abhilash",
"karun",
"hitesh",
)
SARVAM_V3_VOICES = (
"shubh",
"aditya",
"ritu",
"priya",
"neha",
"rahul",
"pooja",
"rohan",
"simran",
"kavya",
"amit",
"dev",
"ishita",
"shreya",
"ratan",
"varun",
"manan",
"sumit",
"roopa",
"kabir",
"aayan",
"ashutosh",
"advait",
"amelia",
"sophia",
"anand",
"tanya",
"tarun",
"sunny",
"mani",
"gokul",
"vijay",
"shruti",
"suhani",
"mohit",
"kavitha",
"rehan",
"soham",
"rupali",
)
SARVAM_LANGUAGES = (
"bn-IN",
"en-IN",
"gu-IN",
"hi-IN",
"kn-IN",
"ml-IN",
"mr-IN",
"od-IN",
"pa-IN",
"ta-IN",
"te-IN",
"as-IN",
)
SARVAM_STT_MODELS = ("saarika:v2.5", "saaras:v2")

63
api/services/configuration/options/speechmatics.py Normal file
View file

@ -0,0 +1,63 @@
SPEECHMATICS_STT_LANGUAGES = (
"ar",
"ar_en",
"ba",
"eu",
"be",
"bn",
"bg",
"yue",
"ca",
"hr",
"cs",
"da",
"nl",
"en",
"eo",
"et",
"fi",
"fr",
"gl",
"de",
"el",
"he",
"hi",
"hu",
"id",
"ia",
"ga",
"it",
"ja",
"ko",
"lv",
"lt",
"ms",
"en_ms",
"mt",
"cmn",
"cmn_en",
"cmn_en_ms_ta",
"mr",
"mn",
"no",
"fa",
"pl",
"pt",
"ro",
"ru",
"sk",
"sl",
"es",
"sw",
"sv",
"tl",
"ta",
"en_ta",
"th",
"tr",
"uk",
"ur",
"ug",
"vi",
"cy",
)

578
api/services/configuration/registry.py
View file

@ -2,7 +2,32 @@ import random
from enum import Enum, auto
from typing import Annotated, Dict, Literal, Type, TypeVar, Union
from pydantic import BaseModel, Field, computed_field, field_validator
from pydantic import BaseModel, ConfigDict, Field, computed_field, field_validator
from api.services.configuration.options import (
DEEPGRAM_LANGUAGES,
DEEPGRAM_STT_MODELS,
GLADIA_STT_LANGUAGES,
GLADIA_STT_MODELS,
GOOGLE_MODELS,
GOOGLE_REALTIME_LANGUAGES,
GOOGLE_REALTIME_MODELS,
GOOGLE_REALTIME_VOICES,
GOOGLE_STT_LANGUAGES,
GOOGLE_STT_MODELS,
GOOGLE_TTS_LANGUAGES,
GOOGLE_TTS_MODELS,
GOOGLE_TTS_VOICES,
GOOGLE_VERTEX_REALTIME_LANGUAGES,
GOOGLE_VERTEX_REALTIME_MODELS,
GOOGLE_VERTEX_REALTIME_VOICES,
SARVAM_LANGUAGES,
SARVAM_STT_MODELS,
SARVAM_TTS_MODELS,
SARVAM_V2_VOICES,
SARVAM_V3_VOICES,
SPEECHMATICS_STT_LANGUAGES,
)
class ServiceType(Enum):
@ -153,9 +178,56 @@ def register_embeddings(cls: Type[BaseEmbeddingsConfiguration]):
return register_service(ServiceType.EMBEDDINGS)(cls)
def provider_model_config(
title: str,
*,
description: str | None = None,
provider_docs_url: str | None = None,
) -> ConfigDict:
json_schema_extra: dict[str, str] = {}
if description is not None:
json_schema_extra["description"] = description
if provider_docs_url is not None:
json_schema_extra["provider_docs_url"] = provider_docs_url
if json_schema_extra:
return ConfigDict(title=title, json_schema_extra=json_schema_extra)
return ConfigDict(title=title)
###################################################### LLM ########################################################################
# Suggested models for each provider (used for UI dropdown)
OPENAI_PROVIDER_MODEL_CONFIG = provider_model_config("OpenAI")
GOOGLE_PROVIDER_MODEL_CONFIG = provider_model_config("Google")
GROQ_PROVIDER_MODEL_CONFIG = provider_model_config("Groq")
OPENROUTER_PROVIDER_MODEL_CONFIG = provider_model_config("Open Router")
AZURE_OPENAI_PROVIDER_MODEL_CONFIG = provider_model_config("Azure OpenAI")
DOGRAH_PROVIDER_MODEL_CONFIG = provider_model_config("Dograh")
AWS_BEDROCK_PROVIDER_MODEL_CONFIG = provider_model_config("AWS Bedrock")
OPENAI_REALTIME_PROVIDER_MODEL_CONFIG = provider_model_config("OpenAI Realtime")
GOOGLE_REALTIME_PROVIDER_MODEL_CONFIG = provider_model_config("Google Realtime")
GOOGLE_VERTEX_REALTIME_PROVIDER_MODEL_CONFIG = provider_model_config(
"Google Vertex Realtime"
)
DEEPGRAM_PROVIDER_MODEL_CONFIG = provider_model_config("Deepgram")
ELEVENLABS_PROVIDER_MODEL_CONFIG = provider_model_config("ElevenLabs")
CARTESIA_PROVIDER_MODEL_CONFIG = provider_model_config("Cartesia")
SARVAM_PROVIDER_MODEL_CONFIG = provider_model_config("Sarvam")
CAMB_PROVIDER_MODEL_CONFIG = provider_model_config("Camb.ai")
RIME_PROVIDER_MODEL_CONFIG = provider_model_config("Rime")
GOOGLE_CLOUD_PROVIDER_MODEL_CONFIG = provider_model_config("Google Cloud")
SPEECHMATICS_PROVIDER_MODEL_CONFIG = provider_model_config("Speechmatics")
ASSEMBLYAI_PROVIDER_MODEL_CONFIG = provider_model_config("AssemblyAI")
GLADIA_PROVIDER_MODEL_CONFIG = provider_model_config("Gladia")
SPEACHES_PROVIDER_MODEL_CONFIG = provider_model_config(
"Local Models (Speaches)",
description=(
"Self-hosted OpenAI-compatible local models. See the Speaches project "
"for setup and supported backends."
),
provider_docs_url="https://github.com/speaches-ai/speaches",
)
OPENAI_MODELS = [
"gpt-4.1",
"gpt-4.1-mini",
@ -165,12 +237,6 @@ OPENAI_MODELS = [
"gpt-5-nano",
"gpt-3.5-turbo",
]
GOOGLE_MODELS = [
"gemini-2.0-flash",
"gemini-2.0-flash-lite",
"gemini-2.5-flash",
"gemini-2.5-flash-lite",
]
GROQ_MODELS = [
"llama-3.3-70b-versatile",
"deepseek-r1-distill-llama-70b",
@ -204,6 +270,7 @@ AWS_BEDROCK_MODELS = [
@register_llm
class OpenAILLMService(BaseLLMConfiguration):
model_config = OPENAI_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI
model: str = Field(
default="gpt-4.1",
@ -214,6 +281,7 @@ class OpenAILLMService(BaseLLMConfiguration):
@register_llm
class GoogleLLMService(BaseLLMConfiguration):
model_config = GOOGLE_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GOOGLE] = ServiceProviders.GOOGLE
model: str = Field(
default="gemini-2.0-flash",
@ -224,6 +292,7 @@ class GoogleLLMService(BaseLLMConfiguration):
@register_llm
class GroqLLMService(BaseLLMConfiguration):
model_config = GROQ_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GROQ] = ServiceProviders.GROQ
model: str = Field(
default="llama-3.3-70b-versatile",
@ -234,6 +303,7 @@ class GroqLLMService(BaseLLMConfiguration):
@register_llm
class OpenRouterLLMConfiguration(BaseLLMConfiguration):
model_config = OPENROUTER_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENROUTER] = ServiceProviders.OPENROUTER
model: str = Field(
default="openai/gpt-4.1",
@ -249,6 +319,7 @@ class OpenRouterLLMConfiguration(BaseLLMConfiguration):
@register_llm
class AzureLLMService(BaseLLMConfiguration):
model_config = AZURE_OPENAI_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.AZURE] = ServiceProviders.AZURE
model: str = Field(
default="gpt-4.1-mini",
@ -263,6 +334,7 @@ class AzureLLMService(BaseLLMConfiguration):
@register_llm
class DograhLLMService(BaseLLMConfiguration):
model_config = DOGRAH_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.DOGRAH] = ServiceProviders.DOGRAH
model: str = Field(
default="default",
@ -273,6 +345,7 @@ class DograhLLMService(BaseLLMConfiguration):
@register_llm
class AWSBedrockLLMConfiguration(BaseLLMConfiguration):
model_config = AWS_BEDROCK_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.AWS_BEDROCK] = ServiceProviders.AWS_BEDROCK
model: str = Field(
default="us.amazon.nova-pro-v1:0",
@ -302,6 +375,7 @@ SPEACHES_LLM_MODELS = ["llama3", "mistral", "phi3", "qwen2", "gemma2", "deepseek
@register_llm
class SpeachesLLMConfiguration(BaseLLMConfiguration):
model_config = SPEACHES_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SPEACHES] = ServiceProviders.SPEACHES
model: str = Field(
default="llama3",
@ -336,6 +410,7 @@ OPENAI_REALTIME_VOICES = [
@register_service(ServiceType.REALTIME)
class OpenAIRealtimeLLMConfiguration(BaseLLMConfiguration):
model_config = OPENAI_REALTIME_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENAI_REALTIME] = (
ServiceProviders.OPENAI_REALTIME
)
@ -357,39 +432,9 @@ class OpenAIRealtimeLLMConfiguration(BaseLLMConfiguration):
)
GOOGLE_REALTIME_MODELS = ["gemini-3.1-flash-live-preview"]
GOOGLE_REALTIME_VOICES = ["Puck", "Charon", "Kore", "Fenrir", "Aoede"]
GOOGLE_REALTIME_LANGUAGES = [
"ar",
"bn",
"de",
"en",
"es",
"fr",
"gu",
"hi",
"id",
"it",
"ja",
"kn",
"ko",
"ml",
"mr",
"nl",
"pl",
"pt",
"ru",
"ta",
"te",
"th",
"tr",
"vi",
"zh",
]
@register_service(ServiceType.REALTIME)
class GoogleRealtimeLLMConfiguration(BaseLLMConfiguration):
model_config = GOOGLE_REALTIME_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GOOGLE_REALTIME] = (
ServiceProviders.GOOGLE_REALTIME
)
@ -419,15 +464,9 @@ class GoogleRealtimeLLMConfiguration(BaseLLMConfiguration):
)
GOOGLE_VERTEX_REALTIME_MODELS = [
"google/gemini-live-2.5-flash-native-audio",
]
GOOGLE_VERTEX_REALTIME_VOICES = GOOGLE_REALTIME_VOICES
GOOGLE_VERTEX_REALTIME_LANGUAGES = GOOGLE_REALTIME_LANGUAGES
@register_service(ServiceType.REALTIME)
class GoogleVertexRealtimeLLMConfiguration(BaseLLMConfiguration):
model_config = GOOGLE_VERTEX_REALTIME_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GOOGLE_VERTEX_REALTIME] = (
ServiceProviders.GOOGLE_VERTEX_REALTIME
)
@ -512,6 +551,7 @@ RealtimeConfig = Annotated[
@register_tts
class DeepgramTTSConfiguration(BaseServiceConfiguration):
model_config = DEEPGRAM_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.DEEPGRAM] = ServiceProviders.DEEPGRAM
voice: str = Field(
default="aura-2-helena-en",
@ -537,6 +577,7 @@ ELEVENLABS_TTS_MODELS = ["eleven_flash_v2_5"]
@register_tts
class ElevenlabsTTSConfiguration(BaseServiceConfiguration):
model_config = ELEVENLABS_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.ELEVENLABS] = ServiceProviders.ELEVENLABS
voice: str = Field(
default="21m00Tcm4TlvDq8ikWAM",
@ -558,11 +599,70 @@ class ElevenlabsTTSConfiguration(BaseServiceConfiguration):
)
@register_tts
class GoogleTTSConfiguration(BaseTTSConfiguration):
model_config = GOOGLE_CLOUD_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GOOGLE] = ServiceProviders.GOOGLE
model: str = Field(
default="chirp_3_hd",
description=(
"Google Cloud low-latency TTS engine. Dograh maps this to Pipecat's "
"streaming Google TTS service for Chirp 3 HD and Journey voices."
),
json_schema_extra={
"examples": GOOGLE_TTS_MODELS,
"allow_custom_input": True,
},
)
voice: str = Field(
default="en-US-Chirp3-HD-Charon",
description="Google Cloud voice name. Use a Chirp 3 HD or Journey voice for streaming TTS.",
json_schema_extra={
"examples": GOOGLE_TTS_VOICES,
"allow_custom_input": True,
},
)
language: str = Field(
default="en-US",
description="BCP-47 language code for synthesis.",
json_schema_extra={
"examples": GOOGLE_TTS_LANGUAGES,
"allow_custom_input": True,
},
)
speed: float = Field(
default=1.0,
ge=0.25,
le=2.0,
description="Speech speed multiplier for Google streaming TTS.",
)
location: str | None = Field(
default=None,
description=(
"Optional Google Cloud regional Text-to-Speech endpoint (for example "
"'us-central1'). Leave blank to use the default endpoint."
),
)
credentials: str | None = Field(
default=None,
description=(
"Paste the entire Google Cloud service-account JSON. If omitted, "
"the server falls back to Application Default Credentials (ADC)."
),
json_schema_extra={"multiline": True},
)
api_key: str | list[str] | None = Field(
default=None,
description="Not used for Google Cloud TTS. Leave blank.",
)
OPENAI_TTS_MODELS = ["gpt-4o-mini-tts"]
@register_tts
class OpenAITTSService(BaseTTSConfiguration):
model_config = OPENAI_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI
model: str = Field(
default="gpt-4o-mini-tts",
@ -580,6 +680,7 @@ DOGRAH_TTS_MODELS = ["default"]
@register_tts
class DograhTTSService(BaseTTSConfiguration):
model_config = DOGRAH_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.DOGRAH] = ServiceProviders.DOGRAH
model: str = Field(
default="default",
@ -598,6 +699,7 @@ CARTESIA_TTS_MODELS = ["sonic-3"]
@register_tts
class CartesiaTTSConfiguration(BaseTTSConfiguration):
model_config = CARTESIA_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.CARTESIA] = ServiceProviders.CARTESIA
model: str = Field(
default="sonic-3",
@ -617,75 +719,9 @@ class CartesiaTTSConfiguration(BaseTTSConfiguration):
)
SARVAM_TTS_MODELS = ["bulbul:v2", "bulbul:v3"]
SARVAM_V2_VOICES = [
"anushka",
"manisha",
"vidya",
"arya",
"abhilash",
"karun",
"hitesh",
]
SARVAM_V3_VOICES = [
"shubh",
"aditya",
"ritu",
"priya",
"neha",
"rahul",
"pooja",
"rohan",
"simran",
"kavya",
"amit",
"dev",
"ishita",
"shreya",
"ratan",
"varun",
"manan",
"sumit",
"roopa",
"kabir",
"aayan",
"ashutosh",
"advait",
"amelia",
"sophia",
"anand",
"tanya",
"tarun",
"sunny",
"mani",
"gokul",
"vijay",
"shruti",
"suhani",
"mohit",
"kavitha",
"rehan",
"soham",
"rupali",
]
SARVAM_LANGUAGES = [
"bn-IN",
"en-IN",
"gu-IN",
"hi-IN",
"kn-IN",
"ml-IN",
"mr-IN",
"od-IN",
"pa-IN",
"ta-IN",
"te-IN",
"as-IN",
]
@register_tts
class SarvamTTSConfiguration(BaseTTSConfiguration):
model_config = SARVAM_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SARVAM] = ServiceProviders.SARVAM
model: str = Field(
default="bulbul:v2",
@ -715,6 +751,7 @@ CAMB_TTS_MODELS = ["mars-flash", "mars-pro", "mars-instruct"]
@register_tts
class CambTTSConfiguration(BaseTTSConfiguration):
model_config = CAMB_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.CAMB] = ServiceProviders.CAMB
model: str = Field(
default="mars-flash",
@ -731,6 +768,7 @@ RIME_TTS_LANGUAGES = ["en", "de", "fr", "es", "hi"]
@register_tts
class RimeTTSConfiguration(BaseTTSConfiguration):
model_config = RIME_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.RIME] = ServiceProviders.RIME
model: str = Field(
default="arcana",
@ -756,6 +794,7 @@ SPEACHES_TTS_MODELS = ["hexgrad/Kokoro-82M"]
@register_tts
class SpeachesTTSConfiguration(BaseTTSConfiguration):
model_config = SPEACHES_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SPEACHES] = ServiceProviders.SPEACHES
model: str = Field(
default="kokoro",
@ -786,6 +825,7 @@ class SpeachesTTSConfiguration(BaseTTSConfiguration):
TTSConfig = Annotated[
Union[
DeepgramTTSConfiguration,
GoogleTTSConfiguration,
OpenAITTSService,
ElevenlabsTTSConfiguration,
CartesiaTTSConfiguration,
@ -801,94 +841,9 @@ TTSConfig = Annotated[
###################################################### STT ########################################################################
DEEPGRAM_STT_MODELS = ["nova-3-general", "flux-general-en", "flux-general-multi"]
DEEPGRAM_LANGUAGES = [
"multi",
"ar",
"ar-AE",
"ar-SA",
"ar-QA",
"ar-KW",
"ar-SY",
"ar-LB",
"ar-PS",
"ar-JO",
"ar-EG",
"ar-SD",
"ar-TD",
"ar-MA",
"ar-DZ",
"ar-TN",
"ar-IQ",
"ar-IR",
"be",
"bn",
"bs",
"bg",
"ca",
"cs",
"da",
"da-DK",
"de",
"de-CH",
"el",
"en",
"en-US",
"en-AU",
"en-GB",
"en-IN",
"en-NZ",
"es",
"es-419",
"et",
"fa",
"fi",
"fr",
"fr-CA",
"he",
"hi",
"hr",
"hu",
"id",
"it",
"ja",
"kn",
"ko",
"ko-KR",
"lt",
"lv",
"mk",
"mr",
"ms",
"nl",
"nl-BE",
"no",
"pl",
"pt",
"pt-BR",
"pt-PT",
"ro",
"ru",
"sk",
"sl",
"sr",
"sv",
"sv-SE",
"ta",
"te",
"th",
"tl",
"tr",
"uk",
"ur",
"vi",
"zh-CN",
"zh-TW",
]
@register_stt
class DeepgramSTTConfiguration(BaseSTTConfiguration):
model_config = DEEPGRAM_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.DEEPGRAM] = ServiceProviders.DEEPGRAM
model: str = Field(
default="nova-3-general",
@ -902,7 +857,7 @@ class DeepgramSTTConfiguration(BaseSTTConfiguration):
"examples": DEEPGRAM_LANGUAGES,
"model_options": {
"nova-3-general": DEEPGRAM_LANGUAGES,
"flux-general-en": ["en"],
"flux-general-en": ("en",),
},
},
)
@ -913,6 +868,7 @@ CARTESIA_STT_MODELS = ["ink-whisper"]
@register_stt
class CartesiaSTTConfiguration(BaseSTTConfiguration):
model_config = CARTESIA_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.CARTESIA] = ServiceProviders.CARTESIA
model: str = Field(
default="ink-whisper",
@ -926,6 +882,7 @@ OPENAI_STT_MODELS = ["gpt-4o-transcribe"]
@register_stt
class OpenAISTTConfiguration(BaseSTTConfiguration):
model_config = OPENAI_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI
model: str = Field(
default="gpt-4o-transcribe",
@ -934,6 +891,45 @@ class OpenAISTTConfiguration(BaseSTTConfiguration):
)
@register_stt
class GoogleSTTConfiguration(BaseSTTConfiguration):
model_config = GOOGLE_CLOUD_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GOOGLE] = ServiceProviders.GOOGLE
model: str = Field(
default="latest_long",
description="Google Cloud Speech-to-Text V2 recognition model.",
json_schema_extra={
"examples": GOOGLE_STT_MODELS,
"allow_custom_input": True,
},
)
language: str = Field(
default="en-US",
description="Primary BCP-47 language code for recognition.",
json_schema_extra={
"examples": GOOGLE_STT_LANGUAGES,
"allow_custom_input": True,
"docs_url": "https://docs.cloud.google.com/speech-to-text/docs/speech-to-text-supported-languages",
},
)
location: str = Field(
default="global",
description="Google Cloud Speech-to-Text region (for example 'global' or 'us-central1').",
)
credentials: str | None = Field(
default=None,
description=(
"Paste the entire Google Cloud service-account JSON. If omitted, "
"the server falls back to Application Default Credentials (ADC)."
),
json_schema_extra={"multiline": True},
)
api_key: str | list[str] | None = Field(
default=None,
description="Not used for Google Cloud STT. Leave blank.",
)
# Dograh STT Service
DOGRAH_STT_MODELS = ["default"]
DOGRAH_STT_LANGUAGES = DEEPGRAM_LANGUAGES
@ -941,6 +937,7 @@ DOGRAH_STT_LANGUAGES = DEEPGRAM_LANGUAGES
@register_stt
class DograhSTTService(BaseSTTConfiguration):
model_config = DOGRAH_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.DOGRAH] = ServiceProviders.DOGRAH
model: str = Field(
default="default",
@ -954,12 +951,9 @@ class DograhSTTService(BaseSTTConfiguration):
)
# Sarvam STT Service
SARVAM_STT_MODELS = ["saarika:v2.5", "saaras:v2"]
@register_stt
class SarvamSTTConfiguration(BaseSTTConfiguration):
model_config = SARVAM_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SARVAM] = ServiceProviders.SARVAM
model: str = Field(
default="saarika:v2.5",
@ -973,74 +967,9 @@ class SarvamSTTConfiguration(BaseSTTConfiguration):
)
# Speechmatics STT Service
SPEECHMATICS_STT_LANGUAGES = [
"ar",
"ar_en",
"ba",
"eu",
"be",
"bn",
"bg",
"yue",
"ca",
"hr",
"cs",
"da",
"nl",
"en",
"eo",
"et",
"fi",
"fr",
"gl",
"de",
"el",
"he",
"hi",
"hu",
"id",
"ia",
"ga",
"it",
"ja",
"ko",
"lv",
"lt",
"ms",
"en_ms",
"mt",
"cmn",
"cmn_en",
"cmn_en_ms_ta",
"mr",
"mn",
"no",
"fa",
"pl",
"pt",
"ro",
"ru",
"sk",
"sl",
"es",
"sw",
"sv",
"tl",
"ta",
"en_ta",
"th",
"tr",
"uk",
"ur",
"ug",
"vi",
"cy",
]
@register_stt
class SpeechmaticsSTTConfiguration(BaseSTTConfiguration):
model_config = SPEECHMATICS_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SPEECHMATICS] = ServiceProviders.SPEECHMATICS
model: str = Field(
default="enhanced",
@ -1062,6 +991,7 @@ SPEACHES_STT_LANGUAGES = ["en", "ar", "nl", "fr", "de", "hi", "it", "pt", "es"]
@register_stt
class SpeachesSTTConfiguration(BaseSTTConfiguration):
model_config = SPEACHES_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SPEACHES] = ServiceProviders.SPEACHES
model: str = Field(
default="Systran/faster-distil-whisper-small.en",
@ -1095,6 +1025,7 @@ ASSEMBLYAI_STT_LANGUAGES = ["en", "es", "de", "fr", "pt", "it"]
@register_stt
class AssemblyAISTTConfiguration(BaseSTTConfiguration):
model_config = ASSEMBLYAI_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.ASSEMBLYAI] = ServiceProviders.ASSEMBLYAI
model: str = Field(
default="u3-rt-pro",
@ -1108,113 +1039,9 @@ class AssemblyAISTTConfiguration(BaseSTTConfiguration):
)
GLADIA_STT_MODELS = ["solaria-1"]
GLADIA_STT_LANGUAGES = [
"af",
"am",
"ar",
"as",
"az",
"ba",
"be",
"bg",
"bn",
"bo",
"br",
"bs",
"ca",
"cs",
"cy",
"da",
"de",
"el",
"en",
"es",
"et",
"eu",
"fa",
"fi",
"fo",
"fr",
"gl",
"gu",
"ha",
"haw",
"he",
"hi",
"hr",
"ht",
"hu",
"hy",
"id",
"is",
"it",
"ja",
"jw",
"ka",
"kk",
"km",
"kn",
"ko",
"la",
"lb",
"ln",
"lo",
"lt",
"lv",
"mg",
"mi",
"mk",
"ml",
"mn",
"mr",
"ms",
"mt",
"my",
"ne",
"nl",
"nn",
"no",
"oc",
"pa",
"pl",
"ps",
"pt",
"ro",
"ru",
"sa",
"sd",
"si",
"sk",
"sl",
"sn",
"so",
"sq",
"sr",
"su",
"sv",
"sw",
"ta",
"te",
"tg",
"th",
"tk",
"tl",
"tr",
"tt",
"uk",
"ur",
"uz",
"vi",
"wo",
"yi",
"yo",
"zh",
]
@register_stt
class GladiaSTTConfiguration(BaseSTTConfiguration):
model_config = GLADIA_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.GLADIA] = ServiceProviders.GLADIA
model: str = Field(
default="solaria-1",
@ -1233,6 +1060,7 @@ STTConfig = Annotated[
DeepgramSTTConfiguration,
CartesiaSTTConfiguration,
OpenAISTTConfiguration,
GoogleSTTConfiguration,
DograhSTTService,
SpeechmaticsSTTConfiguration,
SarvamSTTConfiguration,
@ -1250,6 +1078,7 @@ OPENAI_EMBEDDING_MODELS = ["text-embedding-3-small"]
@register_embeddings
class OpenAIEmbeddingsConfiguration(BaseEmbeddingsConfiguration):
model_config = OPENAI_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENAI] = ServiceProviders.OPENAI
model: str = Field(
default="text-embedding-3-small",
@ -1263,6 +1092,7 @@ OPENROUTER_EMBEDDING_MODELS = ["openai/text-embedding-3-small"]
@register_embeddings
class OpenRouterEmbeddingsConfiguration(BaseEmbeddingsConfiguration):
model_config = OPENROUTER_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.OPENROUTER] = ServiceProviders.OPENROUTER
model: str = Field(
default="openai/text-embedding-3-small",

43
api/services/pipecat/service_factory.py
View file

@ -26,6 +26,8 @@ from pipecat.services.dograh.tts import DograhTTSService, DograhTTSSettings
from pipecat.services.elevenlabs.tts import ElevenLabsTTSService, ElevenLabsTTSSettings
from pipecat.services.gladia.stt import GladiaSTTService, GladiaSTTSettings
from pipecat.services.google.llm import GoogleLLMService, GoogleLLMSettings
from pipecat.services.google.stt import GoogleSTTService, GoogleSTTSettings
from pipecat.services.google.tts import GoogleTTSService, GoogleTTSSettings
from pipecat.services.groq.llm import GroqLLMService, GroqLLMSettings
from pipecat.services.openai.base_llm import OpenAILLMSettings
from pipecat.services.openai.llm import OpenAILLMService
@ -101,6 +103,23 @@ def create_stt_service(
api_key=user_config.stt.api_key,
settings=OpenAISTTSettings(model=user_config.stt.model),
)
elif user_config.stt.provider == ServiceProviders.GOOGLE.value:
language = getattr(user_config.stt, "language", None) or "en-US"
location = getattr(user_config.stt, "location", None) or "global"
credentials = getattr(user_config.stt, "credentials", None)
settings_kwargs = {"model": user_config.stt.model}
try:
settings_kwargs["languages"] = [Language(language)]
except ValueError:
settings_kwargs["language_codes"] = [language]
return GoogleSTTService(
credentials=credentials,
location=location,
settings=GoogleSTTSettings(**settings_kwargs),
sample_rate=audio_config.transport_in_sample_rate,
)
elif user_config.stt.provider == ServiceProviders.CARTESIA.value:
return CartesiaSTTService(
api_key=user_config.stt.api_key,
@ -241,6 +260,30 @@ def create_tts_service(user_config, audio_config: "AudioConfig"):
skip_aggregator_types=["recording_router", "recording"],
silence_time_s=1.0,
)
elif user_config.tts.provider == ServiceProviders.GOOGLE.value:
model = getattr(user_config.tts, "model", None) or "chirp_3_hd"
language = getattr(user_config.tts, "language", None) or "en-US"
voice = getattr(user_config.tts, "voice", None) or "en-US-Chirp3-HD-Charon"
speed = getattr(user_config.tts, "speed", None)
location = getattr(user_config.tts, "location", None) or None
credentials = getattr(user_config.tts, "credentials", None)
settings_kwargs = {
"model": model,
"voice": voice,
"language": language,
}
if speed is not None and speed != 1.0:
settings_kwargs["speaking_rate"] = speed
return GoogleTTSService(
credentials=credentials,
location=location,
settings=GoogleTTSSettings(**settings_kwargs),
text_filters=[xml_function_tag_filter],
skip_aggregator_types=["recording_router", "recording"],
silence_time_s=1.0,
)
elif user_config.tts.provider == ServiceProviders.ELEVENLABS.value:
# Backward compatible with older configuration "Name - voice_id"
try:

5
api/services/workflow/dto.py
View file

@ -610,13 +610,14 @@ class GlobalNodeData(BaseNodeData, _PromptedNodeDataMixin):
"trigger_path": {
"display_name": "Trigger Path",
"description": (
"Auto-generated UUID-style path segment that uniquely identifies "
"Path segment that uniquely identifies "
"this trigger. Used in both URLs:\n"
" • Production: `/api/v1/public/agent/<trigger_path>` — executes "
"the published agent.\n"
" • Test: `/api/v1/public/agent/test/<trigger_path>` — executes "
"the latest draft.\n"
"Do not edit manually."
"Can be customized to a descriptive value up to 36 characters "
"using letters, numbers, hyphens, or underscores."
),
},
},

142
api/services/workflow/trigger_paths.py Normal file
View file

@ -0,0 +1,142 @@
import copy
import re
import uuid
from dataclasses import dataclass
from typing import Optional
TRIGGER_PATH_MAX_LENGTH = 36
TRIGGER_PATH_PATTERN = re.compile(r"^[A-Za-z0-9_-]+$")
@dataclass(frozen=True)
class TriggerPathIssue:
node_id: str | None
trigger_path: str
message: str
def extract_trigger_paths(workflow_definition: Optional[dict]) -> list[str]:
"""Extract trigger paths from a workflow definition."""
if not workflow_definition:
return []
trigger_paths: list[str] = []
for node in workflow_definition.get("nodes") or []:
if node.get("type") != "trigger":
continue
trigger_path = (node.get("data") or {}).get("trigger_path")
if isinstance(trigger_path, str) and trigger_path:
trigger_paths.append(trigger_path)
return trigger_paths
def trigger_path_to_node_id(workflow_definition: Optional[dict]) -> dict[str, str]:
"""Map each trigger node's trigger_path to its node id."""
if not workflow_definition:
return {}
out: dict[str, str] = {}
for node in workflow_definition.get("nodes") or []:
if node.get("type") != "trigger":
continue
trigger_path = (node.get("data") or {}).get("trigger_path")
if isinstance(trigger_path, str) and trigger_path:
out[trigger_path] = node.get("id")
return out
def regenerate_trigger_uuids(workflow_definition: Optional[dict]) -> Optional[dict]:
"""Regenerate UUIDs for all trigger nodes in a workflow definition."""
if not workflow_definition:
return workflow_definition
updated_definition = copy.deepcopy(workflow_definition)
for node in updated_definition.get("nodes") or []:
if node.get("type") != "trigger":
continue
data = node.setdefault("data", {})
data["trigger_path"] = str(uuid.uuid4())
return updated_definition
def ensure_trigger_paths(workflow_definition: Optional[dict]) -> Optional[dict]:
"""Mint UUIDs for trigger nodes that do not already have a path."""
if not workflow_definition:
return workflow_definition
out = copy.deepcopy(workflow_definition)
for node in out.get("nodes") or []:
if node.get("type") != "trigger":
continue
data = node.setdefault("data", {})
if not data.get("trigger_path"):
data["trigger_path"] = str(uuid.uuid4())
return out
def validate_trigger_paths(
workflow_definition: Optional[dict],
) -> list[TriggerPathIssue]:
"""Validate custom trigger paths before they reach persistence/runtime."""
if not workflow_definition:
return []
issues: list[TriggerPathIssue] = []
seen_paths: dict[str, str | None] = {}
for node in workflow_definition.get("nodes") or []:
if node.get("type") != "trigger":
continue
node_id = node.get("id")
trigger_path = (node.get("data") or {}).get("trigger_path")
if not trigger_path:
continue
if not isinstance(trigger_path, str):
issues.append(
TriggerPathIssue(
node_id=node_id,
trigger_path=repr(trigger_path),
message="Trigger path must be a string.",
)
)
continue
if len(trigger_path) > TRIGGER_PATH_MAX_LENGTH:
issues.append(
TriggerPathIssue(
node_id=node_id,
trigger_path=trigger_path,
message=(
f"Trigger path must be {TRIGGER_PATH_MAX_LENGTH} "
"characters or fewer."
),
)
)
if not TRIGGER_PATH_PATTERN.fullmatch(trigger_path):
issues.append(
TriggerPathIssue(
node_id=node_id,
trigger_path=trigger_path,
message=(
"Trigger path must be a single URL path segment using "
"only letters, numbers, hyphens, and underscores."
),
)
)
first_node_id = seen_paths.get(trigger_path)
if first_node_id is None:
seen_paths[trigger_path] = node_id
else:
issues.append(
TriggerPathIssue(
node_id=node_id,
trigger_path=trigger_path,
message="Trigger path is duplicated in this workflow.",
)
)
return issues

55
api/tests/test_google_stt_service_factory.py Normal file
View file

@ -0,0 +1,55 @@
from types import SimpleNamespace
from unittest.mock import patch
from pipecat.transcriptions.language import Language
from api.services.configuration.registry import ServiceProviders
from api.services.pipecat.service_factory import create_stt_service
def test_create_google_stt_service_uses_credentials_location_and_language():
user_config = SimpleNamespace(
stt=SimpleNamespace(
provider=ServiceProviders.GOOGLE.value,
credentials='{"project_id":"demo-project"}',
api_key=None,
model="latest_long",
language="en-US",
location="us-central1",
)
)
audio_config = SimpleNamespace(transport_in_sample_rate=16000)
with patch("api.services.pipecat.service_factory.GoogleSTTService") as mock_service:
create_stt_service(user_config, audio_config)
assert mock_service.call_count == 1
kwargs = mock_service.call_args.kwargs
assert kwargs["credentials"] == '{"project_id":"demo-project"}'
assert kwargs["location"] == "us-central1"
assert kwargs["sample_rate"] == 16000
assert kwargs["settings"].model == "latest_long"
assert kwargs["settings"].languages == [Language.EN_US]
def test_create_google_stt_service_falls_back_to_raw_language_codes():
user_config = SimpleNamespace(
stt=SimpleNamespace(
provider=ServiceProviders.GOOGLE.value,
credentials=None,
api_key=None,
model="chirp_3",
language="cmn-Hans-CN",
location="global",
)
)
audio_config = SimpleNamespace(transport_in_sample_rate=24000)
with patch("api.services.pipecat.service_factory.GoogleSTTService") as mock_service:
create_stt_service(user_config, audio_config)
assert mock_service.call_count == 1
kwargs = mock_service.call_args.kwargs
assert kwargs["sample_rate"] == 24000
assert kwargs["settings"].model == "chirp_3"
assert kwargs["settings"].language_codes == ["cmn-Hans-CN"]

67
api/tests/test_google_tts_service_factory.py Normal file
View file

@ -0,0 +1,67 @@
from types import SimpleNamespace
from unittest.mock import patch
from pipecat.services.settings import NOT_GIVEN
from api.services.configuration.registry import ServiceProviders
from api.services.pipecat.service_factory import create_tts_service
def test_create_google_tts_service_uses_credentials_location_and_settings():
user_config = SimpleNamespace(
tts=SimpleNamespace(
provider=ServiceProviders.GOOGLE.value,
credentials='{"project_id":"demo-project"}',
api_key=None,
model="chirp_3_hd",
voice="en-US-Chirp3-HD-Charon",
language="en-US",
speed=1.15,
location="us-central1",
)
)
audio_config = SimpleNamespace(
transport_out_sample_rate=24000,
transport_in_sample_rate=16000,
)
with patch("api.services.pipecat.service_factory.GoogleTTSService") as mock_service:
create_tts_service(user_config, audio_config)
assert mock_service.call_count == 1
kwargs = mock_service.call_args.kwargs
assert kwargs["credentials"] == '{"project_id":"demo-project"}'
assert kwargs["location"] == "us-central1"
assert kwargs["settings"].model == "chirp_3_hd"
assert kwargs["settings"].voice == "en-US-Chirp3-HD-Charon"
assert kwargs["settings"].language == "en-US"
assert kwargs["settings"].speaking_rate == 1.15
def test_create_google_tts_service_omits_default_speed():
user_config = SimpleNamespace(
tts=SimpleNamespace(
provider=ServiceProviders.GOOGLE.value,
credentials=None,
api_key=None,
model="chirp_3_hd",
voice="en-US-Chirp3-HD-Charon",
language="sw-KE",
speed=1.0,
location=None,
)
)
audio_config = SimpleNamespace(
transport_out_sample_rate=24000,
transport_in_sample_rate=16000,
)
with patch("api.services.pipecat.service_factory.GoogleTTSService") as mock_service:
create_tts_service(user_config, audio_config)
assert mock_service.call_count == 1
kwargs = mock_service.call_args.kwargs
assert kwargs["location"] is None
assert kwargs["settings"].model == "chirp_3_hd"
assert kwargs["settings"].language == "sw-KE"
assert kwargs["settings"].speaking_rate is NOT_GIVEN

39
api/tests/test_mcp_save_workflow.py
View file

@ -186,6 +186,45 @@ const n = wf.addTyped(startCall({ name: "g", prompt: "hi", promt: "typo" }));
update_mock.assert_not_awaited()
@pytest.mark.asyncio
async def test_invalid_trigger_path_surfaces_validation_error(mock_backends):
save_mock, update_mock = mock_backends
payload = {
"nodes": [
{
"id": "trigger-1",
"type": "trigger",
"data": {"trigger_path": "support/west"},
}
],
"edges": [],
}
with (
patch(
"api.mcp_server.tools.save_workflow.parse_code",
AsyncMock(
return_value={
"ok": True,
"workflowName": _FakeWorkflowModel.name,
"workflow": payload,
}
),
),
patch(
"api.mcp_server.tools.save_workflow.reconcile_positions",
return_value=payload,
),
):
result = await save_workflow(workflow_id=1, code="ignored")
assert result["saved"] is False
assert result["error_code"] == "validation_error"
assert "single URL path segment" in result["error"]
save_mock.assert_not_awaited()
update_mock.assert_not_awaited()
# ─── Graph-stage rejections ──────────────────────────────────────────────

191
api/tests/test_public_agent_routes.py Normal file
View file

@ -0,0 +1,191 @@
from types import SimpleNamespace
from unittest.mock import AsyncMock, Mock, patch
from fastapi import FastAPI
from fastapi.testclient import TestClient
from api.routes.public_agent import router
def _make_test_app() -> FastAPI:
app = FastAPI()
app.include_router(router)
return app
def _active_workflow(*, trigger_path: str | None = None):
nodes = []
if trigger_path is not None:
nodes.append(
{
"type": "trigger",
"data": {"trigger_path": trigger_path},
}
)
return SimpleNamespace(
id=33,
user_id=99,
organization_id=11,
status="active",
workflow_uuid="workflow-uuid-123",
released_definition=SimpleNamespace(
workflow_json={"nodes": nodes, "edges": []}
),
)
def _provider():
return SimpleNamespace(
PROVIDER_NAME="twilio",
WEBHOOK_ENDPOINT="outbound",
validate_config=Mock(return_value=True),
initiate_call=AsyncMock(),
)
def test_trigger_route_executes_as_workflow_owner():
app = _make_test_app()
client = TestClient(app)
workflow = _active_workflow(trigger_path="trigger-uuid-123")
provider = _provider()
quota_mock = AsyncMock(
return_value=SimpleNamespace(has_quota=True, error_message="")
)
with (
patch("api.routes.public_agent.db_client") as mock_db,
patch(
"api.routes.public_agent.check_dograh_quota_by_user_id",
new=quota_mock,
),
patch(
"api.routes.public_agent.get_default_telephony_provider",
new=AsyncMock(return_value=provider),
),
patch(
"api.routes.public_agent.get_backend_endpoints",
new=AsyncMock(return_value=("https://api.example.com", "wss://ignored")),
),
):
mock_db.validate_api_key = AsyncMock(
return_value=SimpleNamespace(id=7, organization_id=11, created_by=22)
)
mock_db.get_agent_trigger_by_path = AsyncMock(
return_value=SimpleNamespace(
workflow_id=workflow.id,
organization_id=11,
state="active",
)
)
mock_db.get_workflow = AsyncMock(return_value=workflow)
mock_db.get_default_telephony_configuration = AsyncMock(
return_value=SimpleNamespace(id=55)
)
mock_db.create_workflow_run = AsyncMock(return_value=SimpleNamespace(id=501))
response = client.post(
"/public/agent/trigger-uuid-123",
headers={"X-API-Key": "test-api-key"},
json={"phone_number": "+15551234567"},
)
assert response.status_code == 200
quota_mock.assert_awaited_once_with(workflow.user_id, workflow_id=workflow.id)
mock_db.get_workflow.assert_awaited_once_with(workflow.id, organization_id=11)
create_kwargs = mock_db.create_workflow_run.await_args.kwargs
assert create_kwargs["workflow_id"] == workflow.id
assert create_kwargs["user_id"] == workflow.user_id
assert create_kwargs["organization_id"] == workflow.organization_id
assert create_kwargs["initial_context"]["agent_uuid"] == "trigger-uuid-123"
assert create_kwargs["initial_context"]["agent_identifier"] == "trigger-uuid-123"
assert create_kwargs["initial_context"]["agent_identifier_type"] == "trigger_path"
assert create_kwargs["initial_context"]["workflow_uuid"] == workflow.workflow_uuid
assert create_kwargs["initial_context"]["api_key_id"] == 7
assert create_kwargs["initial_context"]["api_key_created_by"] == 22
initiate_kwargs = provider.initiate_call.await_args.kwargs
assert initiate_kwargs["workflow_id"] == workflow.id
assert initiate_kwargs["user_id"] == workflow.user_id
def test_workflow_uuid_route_uses_scoped_lookup_and_shared_execution():
app = _make_test_app()
client = TestClient(app)
workflow = _active_workflow()
provider = _provider()
quota_mock = AsyncMock(
return_value=SimpleNamespace(has_quota=True, error_message="")
)
with (
patch("api.routes.public_agent.db_client") as mock_db,
patch(
"api.routes.public_agent.check_dograh_quota_by_user_id",
new=quota_mock,
),
patch(
"api.routes.public_agent.get_default_telephony_provider",
new=AsyncMock(return_value=provider),
),
patch(
"api.routes.public_agent.get_backend_endpoints",
new=AsyncMock(return_value=("https://api.example.com", "wss://ignored")),
),
):
mock_db.validate_api_key = AsyncMock(
return_value=SimpleNamespace(id=8, organization_id=11, created_by=22)
)
mock_db.get_workflow_by_uuid = AsyncMock(return_value=workflow)
mock_db.get_default_telephony_configuration = AsyncMock(
return_value=SimpleNamespace(id=55)
)
mock_db.create_workflow_run = AsyncMock(return_value=SimpleNamespace(id=601))
response = client.post(
f"/public/agent/workflow/{workflow.workflow_uuid}",
headers={"X-API-Key": "test-api-key"},
json={"phone_number": "+15551234567"},
)
assert response.status_code == 200
mock_db.get_workflow_by_uuid.assert_awaited_once_with(
workflow.workflow_uuid,
11,
)
assert not mock_db.get_agent_trigger_by_path.called
create_kwargs = mock_db.create_workflow_run.await_args.kwargs
assert create_kwargs["user_id"] == workflow.user_id
assert (
create_kwargs["initial_context"]["agent_identifier"] == workflow.workflow_uuid
)
assert create_kwargs["initial_context"]["agent_identifier_type"] == "workflow_uuid"
assert "agent_uuid" not in create_kwargs["initial_context"]
def test_workflow_uuid_route_rejects_archived_workflows():
app = _make_test_app()
client = TestClient(app)
workflow = _active_workflow()
workflow.status = "archived"
with patch("api.routes.public_agent.db_client") as mock_db:
mock_db.validate_api_key = AsyncMock(
return_value=SimpleNamespace(id=9, organization_id=11, created_by=22)
)
mock_db.get_workflow_by_uuid = AsyncMock(return_value=workflow)
response = client.post(
f"/public/agent/workflow/{workflow.workflow_uuid}",
headers={"X-API-Key": "test-api-key"},
json={"phone_number": "+15551234567"},
)
assert response.status_code == 404
assert response.json()["detail"] == "Workflow is not active"
assert not mock_db.create_workflow_run.called

56
api/tests/test_trigger_path_validation.py Normal file
View file

@ -0,0 +1,56 @@
from api.services.workflow.trigger_paths import (
TRIGGER_PATH_MAX_LENGTH,
validate_trigger_paths,
)
def test_validate_trigger_paths_rejects_invalid_path_segments():
workflow_definition = {
"nodes": [
{
"id": "trigger-1",
"type": "trigger",
"data": {"trigger_path": "support/west"},
}
],
"edges": [],
}
issues = validate_trigger_paths(workflow_definition)
assert len(issues) == 1
assert issues[0].node_id == "trigger-1"
assert "single URL path segment" in issues[0].message
def test_validate_trigger_paths_rejects_long_and_duplicate_paths():
long_path = "a" * (TRIGGER_PATH_MAX_LENGTH + 1)
workflow_definition = {
"nodes": [
{
"id": "trigger-1",
"type": "trigger",
"data": {"trigger_path": long_path},
},
{
"id": "trigger-2",
"type": "trigger",
"data": {"trigger_path": "sales_agent"},
},
{
"id": "trigger-3",
"type": "trigger",
"data": {"trigger_path": "sales_agent"},
},
],
"edges": [],
}
issues = validate_trigger_paths(workflow_definition)
messages = [issue.message for issue in issues]
assert (
f"Trigger path must be {TRIGGER_PATH_MAX_LENGTH} characters or fewer."
in messages
)
assert "Trigger path is duplicated in this workflow." in messages

49
api/tests/test_workflow_create_route.py Normal file
View file

@ -0,0 +1,49 @@
from types import SimpleNamespace
from unittest.mock import patch
from fastapi import FastAPI
from fastapi.testclient import TestClient
from api.routes.workflow import router
from api.services.auth.depends import get_user
def _make_test_app() -> FastAPI:
app = FastAPI()
app.include_router(router)
app.dependency_overrides[get_user] = lambda: SimpleNamespace(
id=1,
provider_id="provider-1",
selected_organization_id=11,
)
return app
def test_create_workflow_rejects_invalid_trigger_path_before_db_write():
app = _make_test_app()
client = TestClient(app)
with patch("api.routes.workflow.db_client") as mock_db:
response = client.post(
"/workflow/create/definition",
json={
"name": "Support Agent",
"workflow_definition": {
"nodes": [
{
"id": "trigger-1",
"type": "trigger",
"data": {"trigger_path": "support/west"},
}
],
"edges": [],
},
},
)
assert response.status_code == 422
detail = response.json()["detail"]
assert detail["is_valid"] is False
assert detail["errors"][0]["field"] == "data.trigger_path"
assert "single URL path segment" in detail["errors"][0]["message"]
assert mock_db.mock_calls == []

52
api/tests/test_workflow_list_route.py Normal file
View file

@ -0,0 +1,52 @@
from datetime import datetime, timezone
from types import SimpleNamespace
from unittest.mock import AsyncMock, patch
from fastapi import FastAPI
from fastapi.testclient import TestClient
from api.routes.workflow import router
from api.services.auth.depends import get_user
def _make_test_app() -> FastAPI:
app = FastAPI()
app.include_router(router)
app.dependency_overrides[get_user] = lambda: SimpleNamespace(
id=1,
selected_organization_id=11,
)
return app
def test_workflow_fetch_list_includes_workflow_uuid():
app = _make_test_app()
client = TestClient(app)
workflow = SimpleNamespace(
id=5,
name="Sales Agent",
status="active",
created_at=datetime(2026, 5, 22, 10, 30, tzinfo=timezone.utc),
folder_id=3,
workflow_uuid="workflow-uuid-123",
)
with patch("api.routes.workflow.db_client") as mock_db:
mock_db.get_all_workflows_for_listing = AsyncMock(return_value=[workflow])
mock_db.get_workflow_run_counts = AsyncMock(return_value={workflow.id: 9})
response = client.get("/workflow/fetch")
assert response.status_code == 200
assert response.json() == [
{
"id": workflow.id,
"name": workflow.name,
"status": workflow.status,
"created_at": "2026-05-22T10:30:00Z",
"total_runs": 9,
"folder_id": workflow.folder_id,
"workflow_uuid": workflow.workflow_uuid,
}
]

8
api/tests/test_workflow_versioning.py
View file

@ -182,7 +182,7 @@ class TestSaveDraft:
workflow_definition=GRAPH_V2,
)
refreshed = await db_session.get_workflow(workflow.id)
refreshed = await db_session.get_workflow_by_id(workflow.id)
assert refreshed.released_definition_id == original_released_id
async def test_save_draft_twice_updates_in_place(
@ -264,7 +264,7 @@ class TestPublishDraft:
await db_session.publish_workflow_draft(workflow.id)
refreshed = await db_session.get_workflow(workflow.id)
refreshed = await db_session.get_workflow_by_id(workflow.id)
assert refreshed.released_definition_id == draft.id
async def test_publish_sets_published_at(self, db_session, workflow_with_v1):
@ -346,7 +346,7 @@ class TestDiscardDraft:
)
await db_session.discard_workflow_draft(workflow.id)
refreshed = await db_session.get_workflow(workflow.id)
refreshed = await db_session.get_workflow_by_id(workflow.id)
assert refreshed.released_definition_id == original_released_id
async def test_discard_when_no_draft_raises(self, db_session, workflow_with_v1):
@ -464,7 +464,7 @@ class TestRevert:
await db_session.revert_to_version(workflow.id, v1_id)
refreshed = await db_session.get_workflow(workflow.id)
refreshed = await db_session.get_workflow_by_id(workflow.id)
assert refreshed.released_definition_id == v2.id # still V2