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Merge branch 'main' into feat/rag-2

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This commit is contained in:
twwu
2025-07-14 11:17:42 +08:00
parent adbad0ad33 d9eb5554b3
commit 682b65034c
325 changed files with 16117 additions and 1288 deletions
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6
api/core/workflow/callbacks/workflow_logging_callback.py
View File

@ -232,14 +232,14 @@ class WorkflowLoggingCallback(WorkflowCallback):
Publish loop started
"""
self.print_text("\n[LoopRunStartedEvent]", color="blue")
self.print_text(f"Loop Node ID: {event.loop_id}", color="blue")
self.print_text(f"Loop Node ID: {event.loop_node_id}", color="blue")
def on_workflow_loop_next(self, event: LoopRunNextEvent) -> None:
"""
Publish loop next
"""
self.print_text("\n[LoopRunNextEvent]", color="blue")
self.print_text(f"Loop Node ID: {event.loop_id}", color="blue")
self.print_text(f"Loop Node ID: {event.loop_node_id}", color="blue")
self.print_text(f"Loop Index: {event.index}", color="blue")
def on_workflow_loop_completed(self, event: LoopRunSucceededEvent | LoopRunFailedEvent) -> None:
@ -250,7 +250,7 @@ class WorkflowLoggingCallback(WorkflowCallback):
"\n[LoopRunSucceededEvent]" if isinstance(event, LoopRunSucceededEvent) else "\n[LoopRunFailedEvent]",
color="blue",
)
self.print_text(f"Node ID: {event.loop_id}", color="blue")
self.print_text(f"Loop Node ID: {event.loop_node_id}", color="blue")
def print_text(self, text: str, color: Optional[str] = None, end: str = "\n") -> None:
"""Print text with highlighting and no end characters."""

2
api/core/workflow/graph_engine/entities/graph.py
View File

@ -336,7 +336,7 @@ class Graph(BaseModel):
parallel = GraphParallel(
start_from_node_id=start_node_id,
parent_parallel_id=parent_parallel.id if parent_parallel else None,
parent_parallel_id=parent_parallel_id,
parent_parallel_start_node_id=parent_parallel.start_from_node_id if parent_parallel else None,
)
parallel_mapping[parallel.id] = parallel

24
api/core/workflow/nodes/agent/agent_node.py
View File

@ -3,11 +3,13 @@ import uuid
from collections.abc import Generator, Mapping, Sequence
from typing import Any, Optional, cast
from packaging.version import Version
from sqlalchemy import select
from sqlalchemy.orm import Session
from core.agent.entities import AgentToolEntity
from core.agent.plugin_entities import AgentStrategyParameter
from core.agent.strategy.plugin import PluginAgentStrategy
from core.memory.token_buffer_memory import TokenBufferMemory
from core.model_manager import ModelInstance, ModelManager
from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
@ -73,12 +75,14 @@ class AgentNode(ToolNode):
agent_parameters=agent_parameters,
variable_pool=self.graph_runtime_state.variable_pool,
node_data=node_data,
strategy=strategy,
)
parameters_for_log = self._generate_agent_parameters(
agent_parameters=agent_parameters,
variable_pool=self.graph_runtime_state.variable_pool,
node_data=node_data,
for_log=True,
strategy=strategy,
)
# get conversation id
@ -155,6 +159,7 @@ class AgentNode(ToolNode):
variable_pool: VariablePool,
node_data: AgentNodeData,
for_log: bool = False,
strategy: PluginAgentStrategy,
) -> dict[str, Any]:
"""
Generate parameters based on the given tool parameters, variable pool, and node data.
@ -207,7 +212,7 @@ class AgentNode(ToolNode):
if parameter.type == "array[tools]":
value = cast(list[dict[str, Any]], value)
value = [tool for tool in value if tool.get("enabled", False)]
value = self._filter_mcp_type_tool(strategy, value)
for tool in value:
if "schemas" in tool:
tool.pop("schemas")
@ -244,9 +249,9 @@ class AgentNode(ToolNode):
)
extra = tool.get("extra", {})
runtime_variable_pool = variable_pool if self.node_data.version != "1" else None
tool_runtime = ToolManager.get_agent_tool_runtime(
self.tenant_id, self.app_id, entity, self.invoke_from
self.tenant_id, self.app_id, entity, self.invoke_from, runtime_variable_pool
)
if tool_runtime.entity.description:
tool_runtime.entity.description.llm = (
@ -398,3 +403,16 @@ class AgentNode(ToolNode):
except ValueError:
model_schema.features.remove(feature)
return model_schema
def _filter_mcp_type_tool(self, strategy: PluginAgentStrategy, tools: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""
Filter MCP type tool
:param strategy: plugin agent strategy
:param tool: tool
:return: filtered tool dict
"""
meta_version = strategy.meta_version
if meta_version and Version(meta_version) > Version("0.0.1"):
return tools
else:
return [tool for tool in tools if tool.get("type") != ToolProviderType.MCP.value]

2
api/core/workflow/nodes/node_mapping.py
View File

@ -75,6 +75,7 @@ NODE_TYPE_CLASSES_MAPPING: Mapping[NodeType, Mapping[str, type[BaseNode]]] = {
},
NodeType.TOOL: {
LATEST_VERSION: ToolNode,
"2": ToolNode,
"1": ToolNode,
},
NodeType.VARIABLE_AGGREGATOR: {
@ -124,6 +125,7 @@ NODE_TYPE_CLASSES_MAPPING: Mapping[NodeType, Mapping[str, type[BaseNode]]] = {
},
NodeType.AGENT: {
LATEST_VERSION: AgentNode,
"2": AgentNode,
"1": AgentNode,
},
NodeType.DATASOURCE: {

23
api/core/workflow/nodes/tool/entities.py
View File

@ -41,6 +41,10 @@ class ToolNodeData(BaseNodeData, ToolEntity):
def check_type(cls, value, validation_info: ValidationInfo):
typ = value
value = validation_info.data.get("value")
if value is None:
return typ
if typ == "mixed" and not isinstance(value, str):
raise ValueError("value must be a string")
elif typ == "variable":
@ -54,3 +58,22 @@ class ToolNodeData(BaseNodeData, ToolEntity):
return typ
tool_parameters: dict[str, ToolInput]
@field_validator("tool_parameters", mode="before")
@classmethod
def filter_none_tool_inputs(cls, value):
if not isinstance(value, dict):
return value
return {
key: tool_input
for key, tool_input in value.items()
if tool_input is not None and cls._has_valid_value(tool_input)
}
@staticmethod
def _has_valid_value(tool_input):
"""Check if the value is valid"""
if isinstance(tool_input, dict):
return tool_input.get("value") is not None
return getattr(tool_input, "value", None) is not None

56
api/core/workflow/nodes/tool/tool_node.py
View File

@ -67,8 +67,9 @@ class ToolNode(BaseNode[ToolNodeData]):
try:
from core.tools.tool_manager import ToolManager
variable_pool = self.graph_runtime_state.variable_pool if self.node_data.version != "1" else None
tool_runtime = ToolManager.get_workflow_tool_runtime(
self.tenant_id, self.app_id, self.node_id, self.node_data, self.invoke_from
self.tenant_id, self.app_id, self.node_id, self.node_data, self.invoke_from, variable_pool
)
except ToolNodeError as e:
yield RunCompletedEvent(
@ -95,7 +96,6 @@ class ToolNode(BaseNode[ToolNodeData]):
node_data=self.node_data,
for_log=True,
)
# get conversation id
conversation_id = self.graph_runtime_state.variable_pool.get(["sys", SystemVariableKey.CONVERSATION_ID])
@ -285,7 +285,8 @@ class ToolNode(BaseNode[ToolNodeData]):
for key, value in msg_metadata.items()
if key in WorkflowNodeExecutionMetadataKey.__members__.values()
}
json.append(message.message.json_object)
if message.message.json_object is not None:
json.append(message.message.json_object)
elif message.type == ToolInvokeMessage.MessageType.LINK:
assert isinstance(message.message, ToolInvokeMessage.TextMessage)
stream_text = f"Link: {message.message.text}\n"
@ -328,6 +329,7 @@ class ToolNode(BaseNode[ToolNodeData]):
icon = current_plugin.declaration.icon
except StopIteration:
pass
icon_dark = None
try:
builtin_tool = next(
provider
@ -338,10 +340,12 @@ class ToolNode(BaseNode[ToolNodeData]):
if provider.name == dict_metadata["provider"]
)
icon = builtin_tool.icon
icon_dark = builtin_tool.icon_dark
except StopIteration:
pass
dict_metadata["icon"] = icon
dict_metadata["icon_dark"] = icon_dark
message.message.metadata = dict_metadata
agent_log = AgentLogEvent(
id=message.message.id,
@ -369,31 +373,31 @@ class ToolNode(BaseNode[ToolNodeData]):
agent_logs.append(agent_log)
yield agent_log
# Add agent_logs to outputs['json'] to ensure frontend can access thinking process
json_output: dict[str, Any] = {}
if json:
if isinstance(json, list) and len(json) == 1:
# If json is a list with only one element, convert it to a dictionary
json_output = json[0] if isinstance(json[0], dict) else {"data": json[0]}
elif isinstance(json, list):
# If json is a list with multiple elements, create a dictionary containing all data
json_output = {"data": json}
# Add agent_logs to outputs['json'] to ensure frontend can access thinking process
json_output: list[dict[str, Any]] = []
# Step 1: append each agent log as its own dict.
if agent_logs:
# Add agent_logs to json output
json_output["agent_logs"] = [
{
"id": log.id,
"parent_id": log.parent_id,
"error": log.error,
"status": log.status,
"data": log.data,
"label": log.label,
"metadata": log.metadata,
"node_id": log.node_id,
}
for log in agent_logs
]
for log in agent_logs:
json_output.append(
{
"id": log.id,
"parent_id": log.parent_id,
"error": log.error,
"status": log.status,
"data": log.data,
"label": log.label,
"metadata": log.metadata,
"node_id": log.node_id,
}
)
# Step 2: normalize JSON into {"data": [...]}.change json to list[dict]
if json:
json_output.extend(json)
else:
json_output.append({"data": []})
yield RunCompletedEvent(
run_result=NodeRunResult(
status=WorkflowNodeExecutionStatus.SUCCEEDED,