mirror of
https://github.com/labring/FastGPT.git
synced 2025-07-22 12:20:34 +00:00
fix: tool choice run same tool will error (#3502)
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@@ -27,9 +27,10 @@ import { getNanoid, sliceStrStartEnd } from '@fastgpt/global/common/string/tools
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import { toolValueTypeList } from '@fastgpt/global/core/workflow/constants';
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import { WorkflowInteractiveResponseType } from '@fastgpt/global/core/workflow/template/system/interactive/type';
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import { ChatItemValueTypeEnum } from '@fastgpt/global/core/chat/constants';
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import { getErrText } from '@fastgpt/global/common/error/utils';
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type ToolRunResponseType = {
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toolRunResponse: DispatchFlowResponse;
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toolRunResponse?: DispatchFlowResponse;
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toolMsgParams: ChatCompletionToolMessageParam;
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}[];
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@@ -344,59 +345,87 @@ export const runToolWithToolChoice = async (
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return Promise.reject(getEmptyResponseTip());
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}
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// Run the selected tool by LLM.
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const toolsRunResponse = (
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await Promise.all(
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toolCalls.map(async (tool) => {
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const toolNode = toolNodes.find((item) => item.nodeId === tool.function?.name);
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/* Run the selected tool by LLM.
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Since only reference parameters are passed, if the same tool is run in parallel, it will get the same run parameters
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*/
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const toolsRunResponse: ToolRunResponseType = [];
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for await (const tool of toolCalls) {
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try {
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const toolNode = toolNodes.find((item) => item.nodeId === tool.function?.name);
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if (!toolNode) return;
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if (!toolNode) continue;
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const startParams = (() => {
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try {
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return json5.parse(tool.function.arguments);
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} catch (error) {
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return {};
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const startParams = (() => {
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try {
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return json5.parse(tool.function.arguments);
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} catch (error) {
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return {};
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}
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})();
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initToolNodes(runtimeNodes, [toolNode.nodeId], startParams);
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const toolRunResponse = await dispatchWorkFlow({
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...workflowProps,
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isToolCall: true
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});
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const stringToolResponse = formatToolResponse(toolRunResponse.toolResponses);
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const toolMsgParams: ChatCompletionToolMessageParam = {
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tool_call_id: tool.id,
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role: ChatCompletionRequestMessageRoleEnum.Tool,
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name: tool.function.name,
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content: stringToolResponse
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};
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workflowStreamResponse?.({
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event: SseResponseEventEnum.toolResponse,
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data: {
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tool: {
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id: tool.id,
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toolName: '',
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toolAvatar: '',
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params: '',
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response: sliceStrStartEnd(stringToolResponse, 5000, 5000)
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}
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})();
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}
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});
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initToolNodes(runtimeNodes, [toolNode.nodeId], startParams);
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const toolRunResponse = await dispatchWorkFlow({
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...workflowProps,
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isToolCall: true
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});
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toolsRunResponse.push({
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toolRunResponse,
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toolMsgParams
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});
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} catch (error) {
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const err = getErrText(error);
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workflowStreamResponse?.({
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event: SseResponseEventEnum.toolResponse,
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data: {
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tool: {
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id: tool.id,
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toolName: '',
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toolAvatar: '',
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params: '',
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response: sliceStrStartEnd(err, 5000, 5000)
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}
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}
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});
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const stringToolResponse = formatToolResponse(toolRunResponse.toolResponses);
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const toolMsgParams: ChatCompletionToolMessageParam = {
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toolsRunResponse.push({
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toolRunResponse: undefined,
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toolMsgParams: {
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tool_call_id: tool.id,
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role: ChatCompletionRequestMessageRoleEnum.Tool,
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name: tool.function.name,
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content: stringToolResponse
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};
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content: sliceStrStartEnd(err, 5000, 5000)
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}
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});
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}
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}
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workflowStreamResponse?.({
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event: SseResponseEventEnum.toolResponse,
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data: {
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tool: {
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id: tool.id,
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toolName: '',
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toolAvatar: '',
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params: '',
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response: sliceStrStartEnd(stringToolResponse, 5000, 5000)
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}
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}
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});
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return {
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toolRunResponse,
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toolMsgParams
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};
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})
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)
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).filter(Boolean) as ToolRunResponseType;
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const flatToolsResponseData = toolsRunResponse.map((item) => item.toolRunResponse).flat();
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const flatToolsResponseData = toolsRunResponse
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.map((item) => item.toolRunResponse)
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.flat()
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.filter(Boolean) as DispatchFlowResponse[];
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// concat tool responses
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const dispatchFlowResponse = response
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? response.dispatchFlowResponse.concat(flatToolsResponseData)
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@@ -434,22 +463,22 @@ export const runToolWithToolChoice = async (
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const outputTokens = await countGptMessagesTokens(assistantToolMsgParams);
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/*
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...
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user
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assistant: tool data
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tool: tool response
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*/
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...
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user
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assistant: tool data
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tool: tool response
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*/
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const completeMessages = [
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...concatToolMessages,
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...toolsRunResponse.map((item) => item?.toolMsgParams)
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];
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/*
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Get tool node assistant response
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history assistant
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current tool assistant
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tool child assistant
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*/
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Get tool node assistant response
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history assistant
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current tool assistant
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tool child assistant
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*/
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const toolNodeAssistant = GPTMessages2Chats([
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...assistantToolMsgParams,
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...toolsRunResponse.map((item) => item?.toolMsgParams)
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@@ -478,12 +507,12 @@ export const runToolWithToolChoice = async (
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);
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// Check interactive response(Only 1 interaction is reserved)
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const workflowInteractiveResponseItem = toolsRunResponse.find(
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(item) => item.toolRunResponse.workflowInteractiveResponse
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(item) => item.toolRunResponse?.workflowInteractiveResponse
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);
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if (hasStopSignal || workflowInteractiveResponseItem) {
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// Get interactive tool data
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const workflowInteractiveResponse =
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workflowInteractiveResponseItem?.toolRunResponse.workflowInteractiveResponse;
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workflowInteractiveResponseItem?.toolRunResponse?.workflowInteractiveResponse;
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// Flashback traverses completeMessages, intercepting messages that know the first user
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const firstUserIndex = completeMessages.findLastIndex((item) => item.role === 'user');
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@@ -72,6 +72,7 @@ import { dispatchLoopEnd } from './loop/runLoopEnd';
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import { dispatchLoopStart } from './loop/runLoopStart';
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import { dispatchFormInput } from './interactive/formInput';
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import { dispatchToolParams } from './agent/runTool/toolParams';
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import { getErrText } from '@fastgpt/global/common/error/utils';
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const callbackMap: Record<FlowNodeTypeEnum, Function> = {
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[FlowNodeTypeEnum.workflowStart]: dispatchWorkflowStart,
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@@ -231,9 +232,7 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
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if (toolResponses !== undefined) {
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if (Array.isArray(toolResponses) && toolResponses.length === 0) return;
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if (typeof toolResponses === 'object' && Object.keys(toolResponses).length === 0) {
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return;
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}
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if (typeof toolResponses === 'object' && Object.keys(toolResponses).length === 0) return;
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toolRunResponse = toolResponses;
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}
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@@ -565,6 +564,8 @@ export async function dispatchWorkFlow(data: Props): Promise<DispatchFlowRespons
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const targetEdges = runtimeEdges.filter((item) => item.source === node.nodeId);
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const skipHandleIds = targetEdges.map((item) => item.sourceHandle);
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toolRunResponse = getErrText(error);
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// Skip all edges and return error
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return {
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[DispatchNodeResponseKeyEnum.nodeResponse]: {
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