Files
dify/api/controllers/openapi/app_run.py
GareArc 6532b4d161 fix(openapi): tighten _DISPATCH return type + cover helper edge cases
- _DISPATCH value type: tuple[Any, dict[str, Any] | None] (was Any, Any).
  Helpers always return one of (stream_obj, None) or (None, dict);
  tightened sig lets mypy flag wrong shapes when Task 3's route handler
  unpacks the result.
- Comment _run_completion's auto_generate_name + query mutations
  (legacy parity; non-obvious without grep-archaeology).
- Unit cover _unpack_blocking (mapping / tuple / non-mapping branches)
  + AppRunRequest.conversation_id field validator (strip-to-None,
  invalid-uuid raise, valid-uuid passthrough).
2026-05-07 00:05:20 -07:00

202 lines
7.3 KiB
Python

"""POST /openapi/v1/apps/<app_id>/run — mode-agnostic runner.
Server reads ``apps.mode`` after AppResolver and dispatches via
_DISPATCH to the per-mode helper. Per-mode constraints (e.g. chat-family
requires ``query``; workflow rejects ``query``) are enforced inside
the helper, post-resolve, since ``mode`` is not in the request body.
"""
from __future__ import annotations
import logging
from collections.abc import Callable, Mapping
from typing import Any, Literal
from uuid import UUID
from pydantic import BaseModel, field_validator
from werkzeug.exceptions import BadRequest, InternalServerError, NotFound, UnprocessableEntity
import services
from controllers.openapi._models import (
ChatMessageResponse,
CompletionMessageResponse,
WorkflowRunResponse,
)
from controllers.service_api.app.error import (
AppUnavailableError,
CompletionRequestError,
ConversationCompletedError,
ProviderModelCurrentlyNotSupportError,
ProviderNotInitializeError,
ProviderQuotaExceededError,
)
from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpError
from core.app.entities.app_invoke_entities import InvokeFrom
from core.errors.error import (
ModelCurrentlyNotSupportError,
ProviderTokenNotInitError,
QuotaExceededError,
)
from graphon.model_runtime.errors.invoke import InvokeError
from libs import helper
from libs.helper import UUIDStrOrEmpty
from models.model import App, AppMode
from services.app_generate_service import AppGenerateService
from services.errors.app import (
IsDraftWorkflowError,
WorkflowIdFormatError,
WorkflowNotFoundError,
)
from services.errors.llm import InvokeRateLimitError
logger = logging.getLogger(__name__)
class AppRunRequest(BaseModel):
inputs: dict[str, Any]
query: str | None = None
files: list[dict[str, Any]] | None = None
response_mode: Literal["blocking", "streaming"] | None = None
conversation_id: UUIDStrOrEmpty | None = None
auto_generate_name: bool = True
workflow_id: str | None = None
@field_validator("conversation_id", mode="before")
@classmethod
def _normalize_conv(cls, value: str | UUID | None) -> str | None:
if isinstance(value, str):
value = value.strip()
if not value:
return None
try:
return helper.uuid_value(value)
except ValueError as exc:
raise ValueError("conversation_id must be a valid UUID") from exc
def _enforce_chat_constraint(payload: AppRunRequest) -> None:
if not payload.query or not payload.query.strip():
raise UnprocessableEntity("query_required_for_chat")
def _enforce_workflow_constraint(payload: AppRunRequest) -> None:
if payload.query is not None:
raise UnprocessableEntity("query_not_supported_for_workflow")
def _unpack_blocking(response: Any) -> Mapping[str, Any]:
if isinstance(response, tuple):
body_dict: Any = response[0]
else:
body_dict = response
if not isinstance(body_dict, Mapping):
raise InternalServerError("blocking generate returned non-mapping response")
return dict(body_dict)
def _generate(app: App, caller: Any, args: dict[str, Any], streaming: bool):
return AppGenerateService.generate(
app_model=app,
user=caller,
args=args,
invoke_from=InvokeFrom.OPENAPI,
streaming=streaming,
)
def _run_chat(app: App, caller: Any, payload: AppRunRequest, streaming: bool):
_enforce_chat_constraint(payload)
args = payload.model_dump(exclude_none=True)
try:
response = _generate(app, caller, args, streaming)
except WorkflowNotFoundError as ex:
raise NotFound(str(ex))
except (IsDraftWorkflowError, WorkflowIdFormatError) as ex:
raise BadRequest(str(ex))
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.conversation.ConversationCompletedError:
raise ConversationCompletedError()
except services.errors.app_model_config.AppModelConfigBrokenError:
logger.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeRateLimitError as ex:
raise InvokeRateLimitHttpError(ex.description)
except InvokeError as e:
raise CompletionRequestError(e.description)
if streaming:
return response, None
body = _unpack_blocking(response)
return None, ChatMessageResponse.model_validate(body).model_dump(mode="json")
def _run_completion(app: App, caller: Any, payload: AppRunRequest, streaming: bool):
args = payload.model_dump(exclude_none=True)
# Completion mode disables auto-naming + tolerates absent query (legacy parity).
args["auto_generate_name"] = False
args.setdefault("query", "")
try:
response = _generate(app, caller, args, streaming)
except services.errors.conversation.ConversationNotExistsError:
raise NotFound("Conversation Not Exists.")
except services.errors.conversation.ConversationCompletedError:
raise ConversationCompletedError()
except services.errors.app_model_config.AppModelConfigBrokenError:
logger.exception("App model config broken.")
raise AppUnavailableError()
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeError as e:
raise CompletionRequestError(e.description)
if streaming:
return response, None
body = _unpack_blocking(response)
return None, CompletionMessageResponse.model_validate(body).model_dump(mode="json")
def _run_workflow(app: App, caller: Any, payload: AppRunRequest, streaming: bool):
_enforce_workflow_constraint(payload)
args = payload.model_dump(exclude={"query", "conversation_id", "auto_generate_name"}, exclude_none=True)
try:
response = _generate(app, caller, args, streaming)
except WorkflowNotFoundError as ex:
raise NotFound(str(ex))
except (IsDraftWorkflowError, WorkflowIdFormatError) as ex:
raise BadRequest(str(ex))
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)
except QuotaExceededError:
raise ProviderQuotaExceededError()
except ModelCurrentlyNotSupportError:
raise ProviderModelCurrentlyNotSupportError()
except InvokeRateLimitError as ex:
raise InvokeRateLimitHttpError(ex.description)
except InvokeError as e:
raise CompletionRequestError(e.description)
if streaming:
return response, None
body = _unpack_blocking(response)
return None, WorkflowRunResponse.model_validate(body).model_dump(mode="json")
_DISPATCH: dict[AppMode, Callable[[App, Any, AppRunRequest, bool], tuple[Any, dict[str, Any] | None]]] = {
AppMode.CHAT: _run_chat,
AppMode.AGENT_CHAT: _run_chat,
AppMode.ADVANCED_CHAT: _run_chat,
AppMode.COMPLETION: _run_completion,
AppMode.WORKFLOW: _run_workflow,
}