mirror of
https://github.com/labring/FastGPT.git
synced 2025-07-21 11:43:56 +00:00
4.8.12 test (#2994)
* perf: run loop code * doc * fix: mulity loop node will error; loop node variables cannot inherit * back save tip position * fix: child workflow runtime * stream connection
This commit is contained in:
@@ -9,6 +9,26 @@ weight: 812
|
||||
|
||||
## 更新指南
|
||||
|
||||
### 1. 做好数据备份
|
||||
|
||||
### 2. 修改镜像
|
||||
|
||||
- 更新 FastGPT 镜像 tag: v4.8.12-beta
|
||||
- 更新 FastGPT 商业版镜像 tag: v4.8.12-beta
|
||||
- Sandbox 镜像,可以不更新
|
||||
|
||||
|
||||
### 3. 商业版执行初始化
|
||||
|
||||
从任意终端,发起 1 个 HTTP 请求。其中 {{rootkey}} 替换成环境变量里的 `rootkey`;{{host}} 替换成**FastGPT 商业版域名**。
|
||||
|
||||
```bash
|
||||
curl --location --request POST 'https://{{host}}/api/admin/init/4812' \
|
||||
--header 'rootkey: {{rootkey}}' \
|
||||
--header 'Content-Type: application/json'
|
||||
```
|
||||
|
||||
会初始化应用和知识库的成员组数据。
|
||||
|
||||
## 更新说明
|
||||
|
||||
@@ -29,3 +49,6 @@ weight: 812
|
||||
15. 修复 - AI 响应为空时,会造成 LLM 历史记录合并。
|
||||
16. 修复 - 用户交互节点未阻塞流程。
|
||||
17. 修复 - 新建 APP,有时候会导致空指针报错。
|
||||
18. 修复 - 拥有多个循环节点时,错误运行。
|
||||
19. 修复 - 循环节点中修改变量,无法传递。
|
||||
20. 修复 - 非 stream 模式,嵌套子应用/插件执行时无法获取子应用响应。
|
||||
|
@@ -18,7 +18,7 @@ export const VariableUpdateNode: FlowNodeTemplateType = {
|
||||
name: i18nT('workflow:variable_update'),
|
||||
intro: i18nT('workflow:update_specified_node_output_or_global_variable'),
|
||||
showStatus: false,
|
||||
isTool: false,
|
||||
isTool: true,
|
||||
version: '481',
|
||||
inputs: [
|
||||
{
|
||||
|
@@ -211,18 +211,7 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
|
||||
});
|
||||
|
||||
// flat child tool response
|
||||
let newVariables: Record<string, any> = props.variables;
|
||||
const childToolResponse = dispatchFlowResponse
|
||||
.map((item) => {
|
||||
// Computed new variables
|
||||
newVariables = {
|
||||
...newVariables,
|
||||
...item.newVariables
|
||||
};
|
||||
|
||||
return item.flowResponses;
|
||||
})
|
||||
.flat();
|
||||
const childToolResponse = dispatchFlowResponse.map((item) => item.flowResponses).flat();
|
||||
|
||||
// concat tool usage
|
||||
const totalPointsUsage =
|
||||
@@ -261,7 +250,6 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
|
||||
},
|
||||
...flatUsages
|
||||
],
|
||||
[DispatchNodeResponseKeyEnum.newVariables]: newVariables,
|
||||
[DispatchNodeResponseKeyEnum.interactive]: toolWorkflowInteractiveResponse
|
||||
};
|
||||
};
|
||||
|
@@ -27,7 +27,7 @@ import { getNanoid, sliceStrStartEnd } from '@fastgpt/global/common/string/tools
|
||||
import { addLog } from '../../../../../common/system/log';
|
||||
import { toolValueTypeList } from '@fastgpt/global/core/workflow/constants';
|
||||
import { WorkflowInteractiveResponseType } from '@fastgpt/global/core/workflow/template/system/interactive/type';
|
||||
import { ChatItemValueTypeEnum, ChatRoleEnum } from '@fastgpt/global/core/chat/constants';
|
||||
import { ChatItemValueTypeEnum } from '@fastgpt/global/core/chat/constants';
|
||||
|
||||
type ToolRunResponseType = {
|
||||
toolRunResponse: DispatchFlowResponse;
|
||||
|
@@ -41,7 +41,8 @@ import { dispatchPluginOutput } from './plugin/runOutput';
|
||||
import { removeSystemVariable, valueTypeFormat } from './utils';
|
||||
import {
|
||||
filterWorkflowEdges,
|
||||
checkNodeRunStatus
|
||||
checkNodeRunStatus,
|
||||
textAdaptGptResponse
|
||||
} from '@fastgpt/global/core/workflow/runtime/utils';
|
||||
import { ChatNodeUsageType } from '@fastgpt/global/support/wallet/bill/type';
|
||||
import { dispatchRunTools } from './agent/runTool/index';
|
||||
@@ -161,6 +162,20 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
|
||||
res.setHeader('Access-Control-Allow-Origin', '*');
|
||||
res.setHeader('X-Accel-Buffering', 'no');
|
||||
res.setHeader('Cache-Control', 'no-cache, no-transform');
|
||||
|
||||
// 10s sends a message to prevent the browser from thinking that the connection is disconnected
|
||||
const sendStreamTimerSign = () => {
|
||||
setTimeout(() => {
|
||||
props?.workflowStreamResponse?.({
|
||||
event: SseResponseEventEnum.answer,
|
||||
data: textAdaptGptResponse({
|
||||
text: ''
|
||||
})
|
||||
});
|
||||
sendStreamTimerSign();
|
||||
}, 10000);
|
||||
};
|
||||
sendStreamTimerSign();
|
||||
}
|
||||
|
||||
variables = {
|
||||
@@ -592,56 +607,60 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
|
||||
};
|
||||
}
|
||||
|
||||
// start process width initInput
|
||||
const entryNodes = runtimeNodes.filter((item) => item.isEntry);
|
||||
// reset entry
|
||||
runtimeNodes.forEach((item) => {
|
||||
// Interactive node is not the entry node, return interactive result
|
||||
if (
|
||||
item.flowNodeType !== FlowNodeTypeEnum.userSelect &&
|
||||
item.flowNodeType !== FlowNodeTypeEnum.formInput &&
|
||||
item.flowNodeType !== FlowNodeTypeEnum.tools
|
||||
) {
|
||||
item.isEntry = false;
|
||||
}
|
||||
});
|
||||
await Promise.all(entryNodes.map((node) => checkNodeCanRun(node)));
|
||||
try {
|
||||
// start process width initInput
|
||||
const entryNodes = runtimeNodes.filter((item) => item.isEntry);
|
||||
// reset entry
|
||||
runtimeNodes.forEach((item) => {
|
||||
// Interactive node is not the entry node, return interactive result
|
||||
if (
|
||||
item.flowNodeType !== FlowNodeTypeEnum.userSelect &&
|
||||
item.flowNodeType !== FlowNodeTypeEnum.formInput &&
|
||||
item.flowNodeType !== FlowNodeTypeEnum.tools
|
||||
) {
|
||||
item.isEntry = false;
|
||||
}
|
||||
});
|
||||
await Promise.all(entryNodes.map((node) => checkNodeCanRun(node)));
|
||||
|
||||
// focus try to run pluginOutput
|
||||
const pluginOutputModule = runtimeNodes.find(
|
||||
(item) => item.flowNodeType === FlowNodeTypeEnum.pluginOutput
|
||||
);
|
||||
if (pluginOutputModule && props.mode !== 'debug') {
|
||||
await nodeRunWithActive(pluginOutputModule);
|
||||
// focus try to run pluginOutput
|
||||
const pluginOutputModule = runtimeNodes.find(
|
||||
(item) => item.flowNodeType === FlowNodeTypeEnum.pluginOutput
|
||||
);
|
||||
if (pluginOutputModule && props.mode !== 'debug') {
|
||||
await nodeRunWithActive(pluginOutputModule);
|
||||
}
|
||||
|
||||
// Interactive node
|
||||
const interactiveResult = (() => {
|
||||
if (nodeInteractiveResponse) {
|
||||
const interactiveAssistant = handleInteractiveResult({
|
||||
entryNodeIds: nodeInteractiveResponse.entryNodeIds,
|
||||
interactiveResponse: nodeInteractiveResponse.interactiveResponse
|
||||
});
|
||||
chatAssistantResponse.push(interactiveAssistant);
|
||||
return interactiveAssistant.interactive;
|
||||
}
|
||||
})();
|
||||
|
||||
return {
|
||||
flowResponses: chatResponses,
|
||||
flowUsages: chatNodeUsages,
|
||||
debugResponse: {
|
||||
finishedNodes: runtimeNodes,
|
||||
finishedEdges: runtimeEdges,
|
||||
nextStepRunNodes: debugNextStepRunNodes
|
||||
},
|
||||
workflowInteractiveResponse: interactiveResult,
|
||||
[DispatchNodeResponseKeyEnum.runTimes]: workflowRunTimes,
|
||||
[DispatchNodeResponseKeyEnum.assistantResponses]:
|
||||
mergeAssistantResponseAnswerText(chatAssistantResponse),
|
||||
[DispatchNodeResponseKeyEnum.toolResponses]: toolRunResponse,
|
||||
newVariables: removeSystemVariable(variables)
|
||||
};
|
||||
} catch (error) {
|
||||
return Promise.reject(error);
|
||||
}
|
||||
|
||||
// Interactive node
|
||||
const interactiveResult = (() => {
|
||||
if (nodeInteractiveResponse) {
|
||||
const interactiveAssistant = handleInteractiveResult({
|
||||
entryNodeIds: nodeInteractiveResponse.entryNodeIds,
|
||||
interactiveResponse: nodeInteractiveResponse.interactiveResponse
|
||||
});
|
||||
chatAssistantResponse.push(interactiveAssistant);
|
||||
return interactiveAssistant.interactive;
|
||||
}
|
||||
})();
|
||||
|
||||
return {
|
||||
flowResponses: chatResponses,
|
||||
flowUsages: chatNodeUsages,
|
||||
debugResponse: {
|
||||
finishedNodes: runtimeNodes,
|
||||
finishedEdges: runtimeEdges,
|
||||
nextStepRunNodes: debugNextStepRunNodes
|
||||
},
|
||||
workflowInteractiveResponse: interactiveResult,
|
||||
[DispatchNodeResponseKeyEnum.runTimes]: workflowRunTimes,
|
||||
[DispatchNodeResponseKeyEnum.assistantResponses]:
|
||||
mergeAssistantResponseAnswerText(chatAssistantResponse),
|
||||
[DispatchNodeResponseKeyEnum.toolResponses]: toolRunResponse,
|
||||
newVariables: removeSystemVariable(variables)
|
||||
};
|
||||
}
|
||||
|
||||
/* get system variable */
|
||||
|
@@ -7,6 +7,7 @@ import {
|
||||
import { dispatchWorkFlow } from '..';
|
||||
import { DispatchNodeResponseKeyEnum } from '@fastgpt/global/core/workflow/runtime/constants';
|
||||
import { AIChatItemValueItemType, ChatHistoryItemResType } from '@fastgpt/global/core/chat/type';
|
||||
import { cloneDeep } from 'lodash';
|
||||
|
||||
type Props = ModuleDispatchProps<{
|
||||
[NodeInputKeyEnum.loopInputArray]: Array<any>;
|
||||
@@ -19,6 +20,7 @@ type Response = DispatchNodeResultType<{
|
||||
export const dispatchLoop = async (props: Props): Promise<Response> => {
|
||||
const {
|
||||
params,
|
||||
runtimeEdges,
|
||||
runtimeNodes,
|
||||
user,
|
||||
node: { name }
|
||||
@@ -28,7 +30,10 @@ export const dispatchLoop = async (props: Props): Promise<Response> => {
|
||||
if (!Array.isArray(loopInputArray)) {
|
||||
return Promise.reject('Input value is not an array');
|
||||
}
|
||||
if (loopInputArray.length > 50) {
|
||||
const maxLength = process.env.WORKFLOW_MAX_LOOP_TIMES
|
||||
? Number(process.env.WORKFLOW_MAX_LOOP_TIMES)
|
||||
: 50;
|
||||
if (loopInputArray.length > maxLength) {
|
||||
return Promise.reject('Input array length cannot be greater than 50');
|
||||
}
|
||||
|
||||
@@ -39,27 +44,25 @@ export const dispatchLoop = async (props: Props): Promise<Response> => {
|
||||
let newVariables: Record<string, any> = props.variables;
|
||||
|
||||
for await (const item of loopInputArray) {
|
||||
runtimeNodes.forEach((node) => {
|
||||
if (
|
||||
childrenNodeIdList.includes(node.nodeId) &&
|
||||
node.flowNodeType === FlowNodeTypeEnum.loopStart
|
||||
) {
|
||||
node.isEntry = true;
|
||||
node.inputs = node.inputs.map((input) =>
|
||||
input.key === NodeInputKeyEnum.loopStartInput
|
||||
? {
|
||||
...input,
|
||||
value: item
|
||||
}
|
||||
: input
|
||||
);
|
||||
}
|
||||
});
|
||||
const response = await dispatchWorkFlow({
|
||||
...props,
|
||||
runtimeNodes: runtimeNodes.map((node) =>
|
||||
node.flowNodeType === FlowNodeTypeEnum.loopStart
|
||||
? {
|
||||
...node,
|
||||
isEntry: true,
|
||||
inputs: node.inputs.map((input) =>
|
||||
input.key === NodeInputKeyEnum.loopStartInput
|
||||
? {
|
||||
...input,
|
||||
value: item
|
||||
}
|
||||
: input
|
||||
)
|
||||
}
|
||||
: {
|
||||
...node,
|
||||
isEntry: false
|
||||
}
|
||||
)
|
||||
runtimeEdges: cloneDeep(runtimeEdges)
|
||||
});
|
||||
|
||||
const loopOutputValue = response.flowResponses.find(
|
||||
|
@@ -113,11 +113,10 @@ export const dispatchRunPlugin = async (props: RunPluginProps): Promise<RunPlugi
|
||||
}
|
||||
|
||||
const usagePoints = await computedPluginUsage(plugin, flowUsages);
|
||||
const childStreamResponse = system_forbid_stream ? false : props.stream;
|
||||
|
||||
return {
|
||||
// 嵌套运行时,如果 childApp stream=false,实际上不会有任何内容输出给用户,所以不需要存储
|
||||
assistantResponses: childStreamResponse ? assistantResponses : [],
|
||||
assistantResponses: system_forbid_stream ? [] : assistantResponses,
|
||||
// responseData, // debug
|
||||
[DispatchNodeResponseKeyEnum.runTimes]: runTimes,
|
||||
[DispatchNodeResponseKeyEnum.nodeResponse]: {
|
||||
|
@@ -124,7 +124,7 @@ export const dispatchRunAppNode = async (props: Props): Promise<Response> => {
|
||||
const usagePoints = flowUsages.reduce((sum, item) => sum + (item.totalPoints || 0), 0);
|
||||
|
||||
return {
|
||||
assistantResponses: childStreamResponse ? assistantResponses : [],
|
||||
assistantResponses: system_forbid_stream ? [] : assistantResponses,
|
||||
[DispatchNodeResponseKeyEnum.runTimes]: runTimes,
|
||||
[DispatchNodeResponseKeyEnum.nodeResponse]: {
|
||||
moduleLogo: appData.avatar,
|
||||
|
@@ -39,4 +39,6 @@ STORE_LOG_LEVEL=warn
|
||||
|
||||
# 安全配置
|
||||
# 工作流最大运行次数,避免极端的死循环情况
|
||||
WORKFLOW_MAX_RUN_TIMES=500
|
||||
WORKFLOW_MAX_RUN_TIMES=500
|
||||
# 循环最大运行次数,避免极端的死循环情况
|
||||
WORKFLOW_MAX_LOOP_TIMES=50
|
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "app",
|
||||
"version": "4.8.11",
|
||||
"version": "4.8.12",
|
||||
"private": false,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
|
@@ -172,7 +172,11 @@ const MoveModal = ({ moveResourceId, title, server, onConfirm, onClose, moveHint
|
||||
onClose={onClose}
|
||||
>
|
||||
<ModalBody flex={'1 0 0'} overflow={'auto'} minH={'400px'}>
|
||||
{moveHint && <LightTip text={moveHint} />}
|
||||
{moveHint && (
|
||||
<Box mb={1}>
|
||||
<LightTip text={moveHint} />
|
||||
</Box>
|
||||
)}
|
||||
<RenderList list={folderList} />
|
||||
</ModalBody>
|
||||
<ModalFooter>
|
||||
|
@@ -34,7 +34,11 @@ const Header = () => {
|
||||
const { t } = useTranslation();
|
||||
const { isPc } = useSystem();
|
||||
const router = useRouter();
|
||||
const { toast } = useToast();
|
||||
const { toast: backSaveToast } = useToast({
|
||||
containerStyle: {
|
||||
mt: '60px'
|
||||
}
|
||||
});
|
||||
|
||||
const { appDetail, onSaveApp, currentTab } = useContextSelector(AppContext, (v) => v);
|
||||
const isV2Workflow = appDetail?.version === 'v2';
|
||||
@@ -273,7 +277,7 @@ const Header = () => {
|
||||
await onClickSave({});
|
||||
onCloseBackConfirm();
|
||||
onBack();
|
||||
toast({
|
||||
backSaveToast({
|
||||
status: 'success',
|
||||
title: t('app:saved_success'),
|
||||
position: 'top-right'
|
||||
|
Reference in New Issue
Block a user