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[Chore/Refactor] Switch from MyPy to Basedpyright for type checking (#25047)

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Signed-off-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
-LAN-
2025-09-03 11:52:26 +08:00
committed by GitHub
parent 1fff4620e6
commit 9d5956cef8
84 changed files with 2380 additions and 2351 deletions
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2
api/core/app/app_config/features/more_like_this/manager.py
View File

@@ -26,7 +26,7 @@ class MoreLikeThisConfigManager:
def validate_and_set_defaults(cls, config: dict) -> tuple[dict, list[str]]:
try:
return AppConfigModel.model_validate(config).model_dump(), ["more_like_this"]
except ValidationError as e:
except ValidationError:
raise ValueError(
"more_like_this must be of dict type and enabled in more_like_this must be of boolean type"
)

37
api/core/app/apps/advanced_chat/generate_task_pipeline.py
View File

@@ -310,13 +310,8 @@ class AdvancedChatAppGenerateTaskPipeline:
err = self._base_task_pipeline._handle_error(event=event, session=session, message_id=self._message_id)
yield self._base_task_pipeline._error_to_stream_response(err)
def _handle_workflow_started_event(
self, event: QueueWorkflowStartedEvent, *, graph_runtime_state: Optional[GraphRuntimeState] = None, **kwargs
) -> Generator[StreamResponse, None, None]:
def _handle_workflow_started_event(self, **kwargs) -> Generator[StreamResponse, None, None]:
"""Handle workflow started events."""
# Override graph runtime state - this is a side effect but necessary
graph_runtime_state = event.graph_runtime_state
with self._database_session() as session:
workflow_execution = self._workflow_cycle_manager.handle_workflow_run_start()
self._workflow_run_id = workflow_execution.id_
@@ -337,15 +332,14 @@ class AdvancedChatAppGenerateTaskPipeline:
"""Handle node retry events."""
self._ensure_workflow_initialized()
with self._database_session() as session:
workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
workflow_execution_id=self._workflow_run_id, event=event
)
node_retry_resp = self._workflow_response_converter.workflow_node_retry_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution,
)
workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
workflow_execution_id=self._workflow_run_id, event=event
)
node_retry_resp = self._workflow_response_converter.workflow_node_retry_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution,
)
if node_retry_resp:
yield node_retry_resp
@@ -379,13 +373,12 @@ class AdvancedChatAppGenerateTaskPipeline:
self._workflow_response_converter.fetch_files_from_node_outputs(event.outputs or {})
)
with self._database_session() as session:
workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_success(event=event)
node_finish_resp = self._workflow_response_converter.workflow_node_finish_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution,
)
workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_success(event=event)
node_finish_resp = self._workflow_response_converter.workflow_node_finish_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution,
)
self._save_output_for_event(event, workflow_node_execution.id)

2
api/core/app/apps/base_app_queue_manager.py
View File

@@ -159,7 +159,7 @@ class AppQueueManager:
def _check_for_sqlalchemy_models(self, data: Any):
# from entity to dict or list
if isinstance(data, dict):
for key, value in data.items():
for value in data.values():
self._check_for_sqlalchemy_models(value)
elif isinstance(data, list):
for item in data:

19
api/core/app/apps/workflow/generate_task_pipeline.py
View File

@@ -300,16 +300,15 @@ class WorkflowAppGenerateTaskPipeline:
"""Handle node retry events."""
self._ensure_workflow_initialized()
with self._database_session() as session:
workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
workflow_execution_id=self._workflow_run_id,
event=event,
)
response = self._workflow_response_converter.workflow_node_retry_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution,
)
workflow_node_execution = self._workflow_cycle_manager.handle_workflow_node_execution_retried(
workflow_execution_id=self._workflow_run_id,
event=event,
)
response = self._workflow_response_converter.workflow_node_retry_to_stream_response(
event=event,
task_id=self._application_generate_entity.task_id,
workflow_node_execution=workflow_node_execution,
)
if response:
yield response

4
api/core/app/entities/app_invoke_entities.py
View File

@@ -1,5 +1,5 @@
from collections.abc import Mapping, Sequence
from enum import Enum
from enum import StrEnum
from typing import Any, Optional
from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_validator
@@ -11,7 +11,7 @@ from core.file import File, FileUploadConfig
from core.model_runtime.entities.model_entities import AIModelEntity
class InvokeFrom(Enum):
class InvokeFrom(StrEnum):
"""
Invoke From.
"""

2
api/core/app/task_pipeline/message_cycle_manager.py
View File

@@ -101,7 +101,7 @@ class MessageCycleManager:
try:
name = LLMGenerator.generate_conversation_name(app_model.tenant_id, query)
conversation.name = name
except Exception as e:
except Exception:
if dify_config.DEBUG:
logger.exception("generate conversation name failed, conversation_id: %s", conversation_id)
pass

2
api/core/callback_handler/index_tool_callback_handler.py
View File

@@ -67,7 +67,7 @@ class DatasetIndexToolCallbackHandler:
)
child_chunk = db.session.scalar(child_chunk_stmt)
if child_chunk:
segment = (
_ = (
db.session.query(DocumentSegment)
.where(DocumentSegment.id == child_chunk.segment_id)
.update(

4
api/core/extension/extensible.py
View File

@@ -91,7 +91,7 @@ class Extensible:
# Find extension class
extension_class = None
for name, obj in vars(mod).items():
for obj in vars(mod).values():
if isinstance(obj, type) and issubclass(obj, cls) and obj != cls:
extension_class = obj
break
@@ -123,7 +123,7 @@ class Extensible:
)
)
except Exception as e:
except Exception:
logger.exception("Error scanning extensions")
raise

6
api/core/extension/extension.py
View File

@@ -41,9 +41,3 @@ class Extension:
assert module_extension.extension_class is not None
t: type = module_extension.extension_class
return t
def validate_form_schema(self, module: ExtensionModule, extension_name: str, config: dict) -> None:
module_extension = self.module_extension(module, extension_name)
form_schema = module_extension.form_schema
# TODO validate form_schema

1
api/core/external_data_tool/factory.py
View File

@@ -22,7 +22,6 @@ class ExternalDataToolFactory:
:param config: the form config data
:return:
"""
code_based_extension.validate_form_schema(ExtensionModule.EXTERNAL_DATA_TOOL, name, config)
extension_class = code_based_extension.extension_class(ExtensionModule.EXTERNAL_DATA_TOOL, name)
# FIXME mypy issue here, figure out how to fix it
extension_class.validate_config(tenant_id, config) # type: ignore

2
api/core/helper/marketplace.py
View File

@@ -42,7 +42,7 @@ def batch_fetch_plugin_manifests_ignore_deserialization_error(
for plugin in response.json()["data"]["plugins"]:
try:
result.append(MarketplacePluginDeclaration(**plugin))
except Exception as e:
except Exception:
pass
return result

3
api/core/indexing_runner.py
View File

@@ -5,7 +5,7 @@ import re
import threading
import time
import uuid
from typing import Any, Optional, cast
from typing import Any, Optional
from flask import current_app
from sqlalchemy import select
@@ -397,7 +397,6 @@ class IndexingRunner:
)
# replace doc id to document model id
text_docs = cast(list[Document], text_docs)
for text_doc in text_docs:
if text_doc.metadata is not None:
text_doc.metadata["document_id"] = dataset_document.id

2
api/core/llm_generator/llm_generator.py
View File

@@ -66,7 +66,7 @@ class LLMGenerator:
try:
result_dict = json.loads(cleaned_answer)
answer = result_dict["Your Output"]
except json.JSONDecodeError as e:
except json.JSONDecodeError:
logger.exception("Failed to generate name after answer, use query instead")
answer = query
name = answer.strip()

4
api/core/mcp/auth/auth_flow.py
View File

@@ -101,7 +101,7 @@ def handle_callback(state_key: str, authorization_code: str) -> OAuthCallbackSta
def check_support_resource_discovery(server_url: str) -> tuple[bool, str]:
"""Check if the server supports OAuth 2.0 Resource Discovery."""
b_scheme, b_netloc, b_path, b_params, b_query, b_fragment = urlparse(server_url, "", True)
b_scheme, b_netloc, b_path, _, b_query, b_fragment = urlparse(server_url, "", True)
url_for_resource_discovery = f"{b_scheme}://{b_netloc}/.well-known/oauth-protected-resource{b_path}"
if b_query:
url_for_resource_discovery += f"?{b_query}"
@@ -117,7 +117,7 @@ def check_support_resource_discovery(server_url: str) -> tuple[bool, str]:
else:
return False, ""
return False, ""
except httpx.RequestError as e:
except httpx.RequestError:
# Not support resource discovery, fall back to well-known OAuth metadata
return False, ""

5
api/core/mcp/mcp_client.py
View File

@@ -2,7 +2,7 @@ import logging
from collections.abc import Callable
from contextlib import AbstractContextManager, ExitStack
from types import TracebackType
from typing import Any, Optional, cast
from typing import Any, Optional
from urllib.parse import urlparse
from core.mcp.client.sse_client import sse_client
@@ -116,8 +116,7 @@ class MCPClient:
self._session_context = ClientSession(*streams)
self._session = self._exit_stack.enter_context(self._session_context)
session = cast(ClientSession, self._session)
session.initialize()
self._session.initialize()
return
except MCPAuthError:

1
api/core/moderation/factory.py
View File

@@ -20,7 +20,6 @@ class ModerationFactory:
:param config: the form config data
:return:
"""
code_based_extension.validate_form_schema(ExtensionModule.MODERATION, name, config)
extension_class = code_based_extension.extension_class(ExtensionModule.MODERATION, name)
# FIXME: mypy error, try to fix it instead of using type: ignore
extension_class.validate_config(tenant_id, config) # type: ignore

2
api/core/moderation/output_moderation.py
View File

@@ -135,7 +135,7 @@ class OutputModeration(BaseModel):
result: ModerationOutputsResult = moderation_factory.moderation_for_outputs(moderation_buffer)
return result
except Exception as e:
except Exception:
logger.exception("Moderation Output error, app_id: %s", app_id)
return None

4
api/core/ops/ops_trace_manager.py
View File

@@ -849,7 +849,7 @@ class TraceQueueManager:
if self.trace_instance:
trace_task.app_id = self.app_id
trace_manager_queue.put(trace_task)
except Exception as e:
except Exception:
logger.exception("Error adding trace task, trace_type %s", trace_task.trace_type)
finally:
self.start_timer()
@@ -868,7 +868,7 @@ class TraceQueueManager:
tasks = self.collect_tasks()
if tasks:
self.send_to_celery(tasks)
except Exception as e:
except Exception:
logger.exception("Error processing trace tasks")
def start_timer(self):

4
api/core/plugin/utils/chunk_merger.py
View File

@@ -1,6 +1,6 @@
from collections.abc import Generator
from dataclasses import dataclass, field
from typing import TypeVar, Union, cast
from typing import TypeVar, Union
from core.agent.entities import AgentInvokeMessage
from core.tools.entities.tool_entities import ToolInvokeMessage
@@ -85,7 +85,7 @@ def merge_blob_chunks(
message=ToolInvokeMessage.BlobMessage(blob=files[chunk_id].data[: files[chunk_id].bytes_written]),
meta=resp.meta,
)
yield cast(MessageType, merged_message)
yield merged_message
# Clean up the buffer
del files[chunk_id]
else:

4
api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
View File

@@ -228,7 +228,7 @@ class AnalyticdbVectorBySql:
)
documents = []
for record in cur:
id, vector, score, page_content, metadata = record
_, vector, score, page_content, metadata = record
if score >= score_threshold:
metadata["score"] = score
doc = Document(
@@ -260,7 +260,7 @@ class AnalyticdbVectorBySql:
)
documents = []
for record in cur:
id, vector, page_content, metadata, score = record
_, vector, page_content, metadata, score = record
metadata["score"] = score
doc = Document(
page_content=page_content,

12
api/core/rag/datasource/vdb/clickzetta/clickzetta_vector.py
View File

@@ -701,7 +701,7 @@ class ClickzettaVector(BaseVector):
len(data_rows),
vector_dimension,
)
except (RuntimeError, ValueError, TypeError, ConnectionError) as e:
except (RuntimeError, ValueError, TypeError, ConnectionError):
logger.exception("Parameterized SQL execution failed for %d documents", len(data_rows))
logger.exception("SQL template: %s", insert_sql)
logger.exception("Sample data row: %s", data_rows[0] if data_rows else "None")
@@ -787,7 +787,7 @@ class ClickzettaVector(BaseVector):
document_ids_filter = kwargs.get("document_ids_filter")
# Handle filter parameter from canvas (workflow)
filter_param = kwargs.get("filter", {})
_ = kwargs.get("filter", {})
# Build filter clause
filter_clauses = []
@@ -879,7 +879,7 @@ class ClickzettaVector(BaseVector):
document_ids_filter = kwargs.get("document_ids_filter")
# Handle filter parameter from canvas (workflow)
filter_param = kwargs.get("filter", {})
_ = kwargs.get("filter", {})
# Build filter clause
filter_clauses = []
@@ -938,7 +938,7 @@ class ClickzettaVector(BaseVector):
metadata = {}
else:
metadata = {}
except (json.JSONDecodeError, TypeError) as e:
except (json.JSONDecodeError, TypeError):
logger.exception("JSON parsing failed")
# Fallback: extract document_id with regex
@@ -956,7 +956,7 @@ class ClickzettaVector(BaseVector):
metadata["score"] = 1.0 # Clickzetta doesn't provide relevance scores
doc = Document(page_content=row[1], metadata=metadata)
documents.append(doc)
except (RuntimeError, ValueError, TypeError, ConnectionError) as e:
except (RuntimeError, ValueError, TypeError, ConnectionError):
logger.exception("Full-text search failed")
# Fallback to LIKE search if full-text search fails
return self._search_by_like(query, **kwargs)
@@ -978,7 +978,7 @@ class ClickzettaVector(BaseVector):
document_ids_filter = kwargs.get("document_ids_filter")
# Handle filter parameter from canvas (workflow)
filter_param = kwargs.get("filter", {})
_ = kwargs.get("filter", {})
# Build filter clause
filter_clauses = []

6
api/core/rag/datasource/vdb/couchbase/couchbase_vector.py
View File

@@ -212,10 +212,10 @@ class CouchbaseVector(BaseVector):
documents_to_insert = [
{"text": text, "embedding": vector, "metadata": metadata}
for id, text, vector, metadata in zip(uuids, texts, embeddings, metadatas)
for _, text, vector, metadata in zip(uuids, texts, embeddings, metadatas)
]
for doc, id in zip(documents_to_insert, uuids):
result = self._scope.collection(self._collection_name).upsert(id, doc)
_ = self._scope.collection(self._collection_name).upsert(id, doc)
doc_ids.extend(uuids)
@@ -241,7 +241,7 @@ class CouchbaseVector(BaseVector):
"""
try:
self._cluster.query(query, named_parameters={"doc_ids": ids}).execute()
except Exception as e:
except Exception:
logger.exception("Failed to delete documents, ids: %s", ids)
def delete_by_document_id(self, document_id: str):

2
api/core/rag/datasource/vdb/matrixone/matrixone_vector.py
View File

@@ -99,7 +99,7 @@ class MatrixoneVector(BaseVector):
return client
try:
client.create_full_text_index()
except Exception as e:
except Exception:
logger.exception("Failed to create full text index")
redis_client.set(collection_exist_cache_key, 1, ex=3600)
return client

2
api/core/rag/datasource/vdb/opensearch/opensearch_vector.py
View File

@@ -197,7 +197,7 @@ class OpenSearchVector(BaseVector):
try:
response = self._client.search(index=self._collection_name.lower(), body=query)
except Exception as e:
except Exception:
logger.exception("Error executing vector search, query: %s", query)
raise

2
api/core/rag/datasource/vdb/tablestore/tablestore_vector.py
View File

@@ -71,7 +71,7 @@ class TableStoreVector(BaseVector):
table_result = result.get_result_by_table(self._table_name)
for item in table_result:
if item.is_ok and item.row:
kv = {k: v for k, v, t in item.row.attribute_columns}
kv = {k: v for k, v, _ in item.row.attribute_columns}
docs.append(
Document(
page_content=kv[Field.CONTENT_KEY.value], metadata=json.loads(kv[Field.METADATA_KEY.value])

2
api/core/rag/extractor/unstructured/unstructured_doc_extractor.py
View File

@@ -23,7 +23,7 @@ class UnstructuredWordExtractor(BaseExtractor):
unstructured_version = tuple(int(x) for x in __unstructured_version__.split("."))
# check the file extension
try:
import magic # noqa: F401
import magic # noqa: F401 # pyright: ignore[reportUnusedImport]
is_doc = detect_filetype(self._file_path) == FileType.DOC
except ImportError:

4
api/core/rag/index_processor/processor/qa_index_processor.py
View File

@@ -113,7 +113,7 @@ class QAIndexProcessor(BaseIndexProcessor):
# Skip the first row
df = pd.read_csv(file)
text_docs = []
for index, row in df.iterrows():
for _, row in df.iterrows():
data = Document(page_content=row.iloc[0], metadata={"answer": row.iloc[1]})
text_docs.append(data)
if len(text_docs) == 0:
@@ -183,7 +183,7 @@ class QAIndexProcessor(BaseIndexProcessor):
qa_document.metadata["doc_hash"] = hash
qa_documents.append(qa_document)
format_documents.extend(qa_documents)
except Exception as e:
except Exception:
logger.exception("Failed to format qa document")
all_qa_documents.extend(format_documents)

12
api/core/rag/retrieval/dataset_retrieval.py
View File

@@ -9,7 +9,6 @@ from typing import Any, Optional, Union, cast
from flask import Flask, current_app
from sqlalchemy import Float, and_, or_, select, text
from sqlalchemy import cast as sqlalchemy_cast
from sqlalchemy.orm import Session
from core.app.app_config.entities import (
DatasetEntity,
@@ -526,7 +525,7 @@ class DatasetRetrieval:
)
child_chunk = db.session.scalar(child_chunk_stmt)
if child_chunk:
segment = (
_ = (
db.session.query(DocumentSegment)
.where(DocumentSegment.id == child_chunk.segment_id)
.update(
@@ -593,9 +592,8 @@ class DatasetRetrieval:
metadata_condition: Optional[MetadataCondition] = None,
):
with flask_app.app_context():
with Session(db.engine) as session:
dataset_stmt = select(Dataset).where(Dataset.id == dataset_id)
dataset = session.scalar(dataset_stmt)
dataset_stmt = select(Dataset).where(Dataset.id == dataset_id)
dataset = db.session.scalar(dataset_stmt)
if not dataset:
return []
@@ -987,7 +985,7 @@ class DatasetRetrieval:
)
# handle invoke result
result_text, usage = self._handle_invoke_result(invoke_result=invoke_result)
result_text, _ = self._handle_invoke_result(invoke_result=invoke_result)
result_text_json = parse_and_check_json_markdown(result_text, [])
automatic_metadata_filters = []
@@ -1002,7 +1000,7 @@ class DatasetRetrieval:
"condition": item.get("comparison_operator"),
}
)
except Exception as e:
except Exception:
return None
return automatic_metadata_filters

2
api/core/rag/retrieval/output_parser/structured_chat.py
View File

@@ -19,5 +19,5 @@ class StructuredChatOutputParser:
return ReactAction(response["action"], response.get("action_input", {}), text)
else:
return ReactFinish({"output": text}, text)
except Exception as e:
except Exception:
raise ValueError(f"Could not parse LLM output: {text}")

2
api/core/rag/retrieval/router/multi_dataset_function_call_router.py
View File

@@ -38,5 +38,5 @@ class FunctionCallMultiDatasetRouter:
# get retrieval model config
return result.message.tool_calls[0].function.name
return None
except Exception as e:
except Exception:
return None

4
api/core/rag/retrieval/router/multi_dataset_react_route.py
View File

@@ -77,7 +77,7 @@ class ReactMultiDatasetRouter:
user_id=user_id,
tenant_id=tenant_id,
)
except Exception as e:
except Exception:
return None
def _react_invoke(
@@ -120,7 +120,7 @@ class ReactMultiDatasetRouter:
memory=None,
model_config=model_config,
)
result_text, usage = self._invoke_llm(
result_text, _ = self._invoke_llm(
completion_param=model_config.parameters,
model_instance=model_instance,
prompt_messages=prompt_messages,

2
api/core/repositories/celery_workflow_execution_repository.py
View File

@@ -119,7 +119,7 @@ class CeleryWorkflowExecutionRepository(WorkflowExecutionRepository):
logger.debug("Queued async save for workflow execution: %s", execution.id_)
except Exception as e:
except Exception:
logger.exception("Failed to queue save operation for execution %s", execution.id_)
# In case of Celery failure, we could implement a fallback to synchronous save
# For now, we'll re-raise the exception

4
api/core/repositories/celery_workflow_node_execution_repository.py
View File

@@ -142,7 +142,7 @@ class CeleryWorkflowNodeExecutionRepository(WorkflowNodeExecutionRepository):
logger.debug("Cached and queued async save for workflow node execution: %s", execution.id)
except Exception as e:
except Exception:
logger.exception("Failed to cache or queue save operation for node execution %s", execution.id)
# In case of Celery failure, we could implement a fallback to synchronous save
# For now, we'll re-raise the exception
@@ -185,6 +185,6 @@ class CeleryWorkflowNodeExecutionRepository(WorkflowNodeExecutionRepository):
logger.debug("Retrieved %d workflow node executions for run %s from cache", len(result), workflow_run_id)
return result
except Exception as e:
except Exception:
logger.exception("Failed to get workflow node executions for run %s from cache", workflow_run_id)
return []

2
api/core/repositories/sqlalchemy_workflow_node_execution_repository.py
View File

@@ -250,7 +250,7 @@ class SQLAlchemyWorkflowNodeExecutionRepository(WorkflowNodeExecutionRepository)
logger.debug("Updating cache for node_execution_id: %s", db_model.node_execution_id)
self._node_execution_cache[db_model.node_execution_id] = db_model
except Exception as e:
except Exception:
logger.exception("Failed to save workflow node execution after all retries")
raise

2
api/core/tools/custom_tool/provider.py
View File

@@ -191,7 +191,7 @@ class ApiToolProviderController(ToolProviderController):
self.tools = tools
return tools
def get_tool(self, tool_name: str):
def get_tool(self, tool_name: str) -> ApiTool:
"""
get tool by name

2
api/core/tools/entities/values.py
View File

@@ -107,5 +107,5 @@ default_tool_label_dict = {
),
}
default_tool_labels = [v for k, v in default_tool_label_dict.items()]
default_tool_labels = list(default_tool_label_dict.values())
default_tool_label_name_list = [label.name for label in default_tool_labels]

17
api/core/tools/tool_manager.py
View File

@@ -303,16 +303,13 @@ class ToolManager:
tenant_id=tenant_id,
controller=api_provider,
)
return cast(
ApiTool,
api_provider.get_tool(tool_name).fork_tool_runtime(
runtime=ToolRuntime(
tenant_id=tenant_id,
credentials=encrypter.decrypt(credentials),
invoke_from=invoke_from,
tool_invoke_from=tool_invoke_from,
)
),
return api_provider.get_tool(tool_name).fork_tool_runtime(
runtime=ToolRuntime(
tenant_id=tenant_id,
credentials=encrypter.decrypt(credentials),
invoke_from=invoke_from,
tool_invoke_from=tool_invoke_from,
)
)
elif provider_type == ToolProviderType.WORKFLOW:
workflow_provider_stmt = select(WorkflowToolProvider).where(

2
api/core/workflow/nodes/answer/answer_stream_processor.py
View File

@@ -68,7 +68,7 @@ class AnswerStreamProcessor(StreamProcessor):
def reset(self) -> None:
self.route_position = {}
for answer_node_id, route_chunks in self.generate_routes.answer_generate_route.items():
for answer_node_id, _ in self.generate_routes.answer_generate_route.items():
self.route_position[answer_node_id] = 0
self.rest_node_ids = self.graph.node_ids.copy()
self.current_stream_chunk_generating_node_ids = {}

6
api/core/workflow/nodes/document_extractor/node.py
View File

@@ -5,7 +5,7 @@ import logging
import os
import tempfile
from collections.abc import Mapping, Sequence
from typing import Any, Optional, cast
from typing import Any, Optional
import chardet
import docx
@@ -428,9 +428,9 @@ def _download_file_content(file: File) -> bytes:
raise FileDownloadError("Missing URL for remote file")
response = ssrf_proxy.get(file.remote_url)
response.raise_for_status()
return cast(bytes, response.content)
return response.content
else:
return cast(bytes, file_manager.download(file))
return file_manager.download(file)
except Exception as e:
raise FileDownloadError(f"Error downloading file: {str(e)}") from e

2
api/core/workflow/nodes/knowledge_retrieval/knowledge_retrieval_node.py
View File

@@ -571,7 +571,7 @@ class KnowledgeRetrievalNode(BaseNode):
"condition": item.get("comparison_operator"),
}
)
except Exception as e:
except Exception:
return []
return automatic_metadata_filters

2
api/core/workflow/nodes/loop/loop_node.py
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@@ -324,7 +324,7 @@ class LoopNode(BaseNode):
# Process conditions if at least one variable is available
if available_conditions:
input_conditions, group_result, check_break_result = condition_processor.process_conditions(
_, _, check_break_result = condition_processor.process_conditions(
variable_pool=self.graph_runtime_state.variable_pool,
conditions=available_conditions,
operator=logical_operator,

4
api/core/workflow/nodes/parameter_extractor/entities.py
View File

@@ -43,10 +43,6 @@ def _validate_type(parameter_type: str) -> SegmentType:
return SegmentType(parameter_type)
class _ParameterConfigError(Exception):
pass
class ParameterConfig(BaseModel):
"""
Parameter Config.

2
api/core/workflow/nodes/variable_assigner/common/helpers.py
View File

@@ -25,7 +25,7 @@ _T = TypeVar("_T", bound=MutableMapping[str, Any])
def variable_to_processed_data(selector: Sequence[str], seg: Segment) -> UpdatedVariable:
if len(selector) < SELECTORS_LENGTH:
raise Exception("selector too short")
node_id, var_name = selector[:2]
_, var_name = selector[:2]
return UpdatedVariable(
name=var_name,
selector=list(selector[:2]),