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feat(sandbox): skill initialize & draft run

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Harry
2026-01-19 18:15:24 +08:00
parent 3bb9c4b280
commit 956436b943
18 changed files with 531 additions and 280 deletions
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42
api/core/workflow/nodes/llm/node.py
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@ -13,7 +13,7 @@ from sqlalchemy import select
from core.agent.entities import AgentEntity, AgentLog, AgentResult, AgentToolEntity, ExecutionContext
from core.agent.patterns import StrategyFactory
from core.app.entities.app_invoke_entities import InvokeFrom, ModelConfigWithCredentialsEntity
from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
from core.file import File, FileTransferMethod, FileType, file_manager
from core.helper.code_executor import CodeExecutor, CodeLanguage
from core.llm_generator.output_parser.errors import OutputParserError
@ -1580,34 +1580,17 @@ class LLMNode(Node[LLMNodeData]):
result = yield from self._process_tool_outputs(outputs)
return result
def _prepare_sandbox_tools(self) -> list[Tool]:
"""Prepare sandbox tools."""
tool_instances = []
def _get_allow_tools_list(self) -> list[str] | None:
if not self._node_data.tools:
return None
for tool in self._node_data.tools or []:
try:
# Get tool runtime from ToolManager
tool_runtime = ToolManager.get_tool_runtime(
tenant_id=self.tenant_id,
tool_name=tool.tool_name,
provider_id=tool.provider_name,
provider_type=tool.type,
invoke_from=InvokeFrom.AGENT,
credential_id=tool.credential_id,
)
allow_tools = []
for tool in self._node_data.tools:
if tool.enabled:
tool_name = f"{tool.tool_name}"
allow_tools.append(tool_name)
# Apply custom description from extra field if available
if tool.extra.get("description") and tool_runtime.entity.description:
tool_runtime.entity.description.llm = (
tool.extra.get("description") or tool_runtime.entity.description.llm
)
tool_instances.append(tool_runtime)
except Exception as e:
logger.warning("Failed to load tool %s: %s", tool, str(e))
continue
return tool_instances
return allow_tools or None
def _invoke_llm_with_sandbox(
self,
@ -1620,7 +1603,7 @@ class LLMNode(Node[LLMNodeData]):
if not workflow_execution_id:
raise LLMNodeError("workflow_execution_id is required for sandbox runtime mode")
configured_tools = self._prepare_sandbox_tools()
allow_tools = self._get_allow_tools_list()
result: LLMGenerationData | None = None
@ -1628,7 +1611,8 @@ class LLMNode(Node[LLMNodeData]):
workflow_execution_id=workflow_execution_id,
tenant_id=self.tenant_id,
user_id=self.user_id,
tools=configured_tools,
node_id=self.id,
allow_tools=allow_tools,
) as sandbox_session:
prompt_files = self._extract_prompt_files(variable_pool)
model_features = self._get_model_features(model_instance)