mirror of
https://github.com/langgenius/dify.git
synced 2026-09-24 23:22:26 +08:00
feat(dify-agent): sync agent progress (#36633)
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
This commit is contained in:
盐粒 Yanli
co-authored by
autofix-ci[bot]
autofix-ci[bot]
parent
884e2b864b
commit
0f06aa2fdd
@@ -22,9 +22,6 @@ from core.memory.token_buffer_memory import TokenBufferMemory
|
||||
from core.model_manager import ModelInstance
|
||||
from core.prompt.utils.extract_thread_messages import extract_thread_messages
|
||||
from core.tools.__base.tool import Tool
|
||||
from core.tools.entities.tool_entities import (
|
||||
ToolParameter,
|
||||
)
|
||||
from core.tools.tool_manager import ToolManager
|
||||
from core.tools.utils.dataset_retriever_tool import DatasetRetrieverTool
|
||||
from extensions.ext_database import db
|
||||
@@ -150,44 +147,9 @@ class BaseAgentRunner(AppRunner):
|
||||
message_tool = PromptMessageTool(
|
||||
name=tool.tool_name,
|
||||
description=tool_entity.entity.description.llm,
|
||||
parameters={
|
||||
"type": "object",
|
||||
"properties": {},
|
||||
"required": [],
|
||||
},
|
||||
parameters=tool_entity.get_llm_parameters_json_schema(),
|
||||
)
|
||||
|
||||
parameters = tool_entity.get_merged_runtime_parameters()
|
||||
for parameter in parameters:
|
||||
if parameter.form != ToolParameter.ToolParameterForm.LLM:
|
||||
continue
|
||||
|
||||
parameter_type = parameter.type.as_normal_type()
|
||||
if parameter.type in {
|
||||
ToolParameter.ToolParameterType.SYSTEM_FILES,
|
||||
ToolParameter.ToolParameterType.FILE,
|
||||
ToolParameter.ToolParameterType.FILES,
|
||||
}:
|
||||
continue
|
||||
enum = []
|
||||
if parameter.type == ToolParameter.ToolParameterType.SELECT:
|
||||
enum = [option.value for option in parameter.options] if parameter.options else []
|
||||
|
||||
message_tool.parameters["properties"][parameter.name] = (
|
||||
{
|
||||
"type": parameter_type,
|
||||
"description": parameter.llm_description or "",
|
||||
}
|
||||
if parameter.input_schema is None
|
||||
else parameter.input_schema
|
||||
)
|
||||
|
||||
if len(enum) > 0:
|
||||
message_tool.parameters["properties"][parameter.name]["enum"] = enum
|
||||
|
||||
if parameter.required:
|
||||
message_tool.parameters["required"].append(parameter.name)
|
||||
|
||||
return message_tool, tool_entity
|
||||
|
||||
def _convert_dataset_retriever_tool_to_prompt_message_tool(self, tool: DatasetRetrieverTool) -> PromptMessageTool:
|
||||
@@ -252,40 +214,7 @@ class BaseAgentRunner(AppRunner):
|
||||
"""
|
||||
update prompt message tool
|
||||
"""
|
||||
# try to get tool runtime parameters
|
||||
tool_runtime_parameters = tool.get_runtime_parameters()
|
||||
|
||||
for parameter in tool_runtime_parameters:
|
||||
if parameter.form != ToolParameter.ToolParameterForm.LLM:
|
||||
continue
|
||||
|
||||
parameter_type = parameter.type.as_normal_type()
|
||||
if parameter.type in {
|
||||
ToolParameter.ToolParameterType.SYSTEM_FILES,
|
||||
ToolParameter.ToolParameterType.FILE,
|
||||
ToolParameter.ToolParameterType.FILES,
|
||||
}:
|
||||
continue
|
||||
enum = []
|
||||
if parameter.type == ToolParameter.ToolParameterType.SELECT:
|
||||
enum = [option.value for option in parameter.options] if parameter.options else []
|
||||
|
||||
prompt_tool.parameters["properties"][parameter.name] = (
|
||||
{
|
||||
"type": parameter_type,
|
||||
"description": parameter.llm_description or "",
|
||||
}
|
||||
if parameter.input_schema is None
|
||||
else parameter.input_schema
|
||||
)
|
||||
|
||||
if len(enum) > 0:
|
||||
prompt_tool.parameters["properties"][parameter.name]["enum"] = enum
|
||||
|
||||
if parameter.required:
|
||||
if parameter.name not in prompt_tool.parameters["required"]:
|
||||
prompt_tool.parameters["required"].append(parameter.name)
|
||||
|
||||
prompt_tool.parameters = tool.get_llm_parameters_json_schema()
|
||||
return prompt_tool
|
||||
|
||||
def create_agent_thought(
|
||||
|
||||
@@ -126,34 +126,89 @@ class Tool(ABC):
|
||||
message_id: str | None = None,
|
||||
) -> list[ToolParameter]:
|
||||
"""
|
||||
get merged runtime parameters
|
||||
Get the effective parameter declarations for this tool.
|
||||
|
||||
Runtime parameters override declared parameters by name and append new
|
||||
parameters, but the returned list is always detached from the tool's
|
||||
cached declarations so callers can safely mutate it while building
|
||||
downstream schemas.
|
||||
|
||||
:return: merged runtime parameters
|
||||
"""
|
||||
parameters = self.entity.parameters
|
||||
parameters = parameters.copy()
|
||||
user_parameters = self.get_runtime_parameters() or []
|
||||
user_parameters = user_parameters.copy()
|
||||
parameters = [deepcopy(parameter) for parameter in self.entity.parameters or []]
|
||||
user_parameters = [
|
||||
deepcopy(parameter)
|
||||
for parameter in self.get_runtime_parameters(
|
||||
conversation_id=conversation_id,
|
||||
app_id=app_id,
|
||||
message_id=message_id,
|
||||
)
|
||||
or []
|
||||
]
|
||||
|
||||
parameter_indexes = {parameter.name: index for index, parameter in enumerate(parameters)}
|
||||
|
||||
# override parameters
|
||||
for parameter in user_parameters:
|
||||
# check if parameter in tool parameters
|
||||
for tool_parameter in parameters:
|
||||
if tool_parameter.name == parameter.name:
|
||||
# override parameter
|
||||
tool_parameter.type = parameter.type
|
||||
tool_parameter.form = parameter.form
|
||||
tool_parameter.required = parameter.required
|
||||
tool_parameter.default = parameter.default
|
||||
tool_parameter.options = parameter.options
|
||||
tool_parameter.llm_description = parameter.llm_description
|
||||
break
|
||||
else:
|
||||
# add new parameter
|
||||
existing_index = parameter_indexes.get(parameter.name)
|
||||
if existing_index is None:
|
||||
parameter_indexes[parameter.name] = len(parameters)
|
||||
parameters.append(parameter)
|
||||
continue
|
||||
parameters[existing_index] = parameter
|
||||
|
||||
return parameters
|
||||
|
||||
def get_llm_parameters_json_schema(
|
||||
self,
|
||||
conversation_id: str | None = None,
|
||||
app_id: str | None = None,
|
||||
message_id: str | None = None,
|
||||
) -> dict[str, Any]:
|
||||
"""Build the model-visible JSON schema from effective tool parameters.
|
||||
|
||||
Hidden/manual parameters stay available for invocation preparation on the
|
||||
API side, but are intentionally omitted from the LLM-facing schema.
|
||||
"""
|
||||
schema: dict[str, Any] = {
|
||||
"type": "object",
|
||||
"properties": {},
|
||||
"required": [],
|
||||
}
|
||||
|
||||
for parameter in self.get_merged_runtime_parameters(
|
||||
conversation_id=conversation_id,
|
||||
app_id=app_id,
|
||||
message_id=message_id,
|
||||
):
|
||||
if parameter.form != ToolParameter.ToolParameterForm.LLM:
|
||||
continue
|
||||
|
||||
if parameter.type in {
|
||||
ToolParameter.ToolParameterType.SYSTEM_FILES,
|
||||
ToolParameter.ToolParameterType.FILE,
|
||||
ToolParameter.ToolParameterType.FILES,
|
||||
}:
|
||||
continue
|
||||
|
||||
parameter_schema: dict[str, Any] = (
|
||||
{
|
||||
"type": parameter.type.as_normal_type(),
|
||||
"description": parameter.llm_description or "",
|
||||
}
|
||||
if parameter.input_schema is None
|
||||
else deepcopy(parameter.input_schema)
|
||||
)
|
||||
parameter_schema.setdefault("description", parameter.llm_description or "")
|
||||
|
||||
if parameter.type == ToolParameter.ToolParameterType.SELECT and parameter.options:
|
||||
parameter_schema["enum"] = [option.value for option in parameter.options]
|
||||
|
||||
schema["properties"][parameter.name] = parameter_schema
|
||||
if parameter.required:
|
||||
schema["required"].append(parameter.name)
|
||||
|
||||
return schema
|
||||
|
||||
def create_image_message(
|
||||
self,
|
||||
image: str,
|
||||
|
||||
@@ -4,7 +4,8 @@ from collections.abc import Mapping, Sequence
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Literal, Protocol, cast
|
||||
|
||||
from dify_agent.protocol import CreateRunRequest, ExecutionContext
|
||||
from dify_agent.layers.execution_context import DifyExecutionContextLayerConfig
|
||||
from dify_agent.protocol import CreateRunRequest
|
||||
|
||||
from clients.agent_backend import (
|
||||
AgentBackendModelConfig,
|
||||
@@ -105,16 +106,20 @@ class WorkflowAgentRuntimeRequestBuilder:
|
||||
request = self._request_builder.build_for_workflow_node(
|
||||
AgentBackendWorkflowNodeRunInput(
|
||||
model=AgentBackendModelConfig(
|
||||
tenant_id=context.dify_context.tenant_id,
|
||||
plugin_id=agent_soul.model.plugin_id,
|
||||
model_provider=agent_soul.model.model_provider,
|
||||
model=agent_soul.model.model,
|
||||
user_id=context.dify_context.user_id,
|
||||
credentials=self._normalize_credentials(credentials),
|
||||
model_settings=cast(dict[str, Any], agent_soul.model.model_settings),
|
||||
),
|
||||
execution_context=ExecutionContext(
|
||||
# The execution-context layer is now the only public protocol
|
||||
# carrier for Dify tenant/user/run identifiers. ``user_id`` must
|
||||
# be forwarded here because downstream plugin-daemon provider and
|
||||
# tool clients read it from this layer rather than from any
|
||||
# parallel top-level request field.
|
||||
execution_context=DifyExecutionContextLayerConfig(
|
||||
tenant_id=context.dify_context.tenant_id,
|
||||
user_id=context.dify_context.user_id,
|
||||
app_id=context.dify_context.app_id,
|
||||
workflow_id=context.workflow_id,
|
||||
workflow_run_id=context.workflow_run_id,
|
||||
|
||||
Reference in New Issue
Block a user