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Chore/Update issue templates and add new tools (#4687)
* Enhancement: Update issue templates and add new tools - Updated bug report template to include a default label of 'bug'. - Updated feature request template to include a default label of 'enhancement'. - Added new credential class for Agentflow API. - Enhanced Agent and HTTP nodes to improve tool management and error handling. - Added deprecation badges to several agent and chain classes. - Introduced new tools for handling requests (GET, POST, DELETE, PUT) with improved error handling. - Added new chatflows and agentflows for various use cases, including document QnA and translation. - Updated UI components for better handling of agent flows and marketplace interactions. - Refactored utility functions for improved functionality and clarity. * Refactor: Remove beta badge and streamline template title assignment - Removed the 'BETA' badge from the ExtractMetadataRetriever class. - Simplified the title assignment in the agentflowv2 generator by using a variable instead of inline string manipulation.
This commit is contained in:
Henry Heng
@@ -0,0 +1,628 @@
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{
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"description": "A basic RAG agent that can retrieve documents from document store and answer questions",
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"usecases": ["Documents QnA"],
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"nodes": [
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{
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"id": "startAgentflow_0",
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"type": "agentFlow",
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"position": {
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"x": 64,
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"y": 98.5
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},
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"data": {
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"id": "startAgentflow_0",
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"label": "Start",
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"version": 1.1,
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"name": "startAgentflow",
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"type": "Start",
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"color": "#7EE787",
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"hideInput": true,
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"baseClasses": ["Start"],
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"category": "Agent Flows",
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"description": "Starting point of the agentflow",
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"inputParams": [
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{
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"label": "Input Type",
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"name": "startInputType",
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"type": "options",
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"options": [
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{
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"label": "Chat Input",
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"name": "chatInput",
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"description": "Start the conversation with chat input"
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},
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{
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"label": "Form Input",
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"name": "formInput",
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"description": "Start the workflow with form inputs"
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}
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],
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"default": "chatInput",
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"id": "startAgentflow_0-input-startInputType-options",
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"display": true
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},
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{
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"label": "Form Title",
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"name": "formTitle",
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"type": "string",
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"placeholder": "Please Fill Out The Form",
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"show": {
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"startInputType": "formInput"
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},
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"id": "startAgentflow_0-input-formTitle-string",
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"display": false
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},
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{
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"label": "Form Description",
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"name": "formDescription",
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"type": "string",
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"placeholder": "Complete all fields below to continue",
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"show": {
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"startInputType": "formInput"
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},
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"id": "startAgentflow_0-input-formDescription-string",
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"display": false
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},
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{
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"label": "Form Input Types",
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"name": "formInputTypes",
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"description": "Specify the type of form input",
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"type": "array",
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"show": {
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"startInputType": "formInput"
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},
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"array": [
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{
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"label": "Type",
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"name": "type",
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"type": "options",
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"options": [
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{
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"label": "String",
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"name": "string"
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},
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{
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"label": "Number",
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"name": "number"
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},
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{
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"label": "Boolean",
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"name": "boolean"
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},
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{
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"label": "Options",
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"name": "options"
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}
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],
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"default": "string"
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},
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{
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"label": "Label",
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"name": "label",
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"type": "string",
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"placeholder": "Label for the input"
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},
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{
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"label": "Variable Name",
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"name": "name",
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"type": "string",
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"placeholder": "Variable name for the input (must be camel case)",
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"description": "Variable name must be camel case. For example: firstName, lastName, etc."
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},
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{
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"label": "Add Options",
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"name": "addOptions",
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"type": "array",
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"show": {
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"formInputTypes[$index].type": "options"
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},
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"array": [
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{
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"label": "Option",
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"name": "option",
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"type": "string"
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}
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]
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}
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],
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"id": "startAgentflow_0-input-formInputTypes-array",
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"display": false
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},
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{
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"label": "Ephemeral Memory",
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"name": "startEphemeralMemory",
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"type": "boolean",
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"description": "Start fresh for every execution without past chat history",
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"optional": true,
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"id": "startAgentflow_0-input-startEphemeralMemory-boolean",
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"display": true
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},
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{
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"label": "Flow State",
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"name": "startState",
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"description": "Runtime state during the execution of the workflow",
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"type": "array",
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"optional": true,
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"array": [
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{
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"label": "Key",
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"name": "key",
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"type": "string",
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"placeholder": "Foo"
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},
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{
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"label": "Value",
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"name": "value",
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"type": "string",
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"placeholder": "Bar",
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"optional": true
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}
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],
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"id": "startAgentflow_0-input-startState-array",
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"display": true
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},
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{
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"label": "Persist State",
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"name": "startPersistState",
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"type": "boolean",
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"description": "Persist the state in the same session",
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"optional": true,
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"id": "startAgentflow_0-input-startPersistState-boolean",
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"display": true
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}
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],
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"inputAnchors": [],
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"inputs": {
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"startInputType": "chatInput",
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"formTitle": "",
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"formDescription": "",
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"formInputTypes": "",
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"startEphemeralMemory": "",
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"startState": "",
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"startPersistState": ""
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},
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"outputAnchors": [
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{
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"id": "startAgentflow_0-output-startAgentflow",
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"label": "Start",
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"name": "startAgentflow"
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}
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],
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"outputs": {},
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"selected": false
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},
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"width": 103,
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"height": 66,
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"positionAbsolute": {
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"x": 64,
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"y": 98.5
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},
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"selected": false,
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"dragging": false
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},
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{
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"id": "agentAgentflow_0",
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"position": {
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"x": 216.75,
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"y": 96.5
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},
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"data": {
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"id": "agentAgentflow_0",
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"label": "QnA",
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"version": 1,
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"name": "agentAgentflow",
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"type": "Agent",
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"color": "#4DD0E1",
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"baseClasses": ["Agent"],
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"category": "Agent Flows",
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"description": "Dynamically choose and utilize tools during runtime, enabling multi-step reasoning",
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"inputParams": [
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{
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"label": "Model",
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"name": "agentModel",
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"type": "asyncOptions",
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"loadMethod": "listModels",
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"loadConfig": true,
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"id": "agentAgentflow_0-input-agentModel-asyncOptions",
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"display": true
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},
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{
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"label": "Messages",
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"name": "agentMessages",
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"type": "array",
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"optional": true,
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"acceptVariable": true,
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"array": [
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{
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"label": "Role",
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"name": "role",
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"type": "options",
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"options": [
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{
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"label": "System",
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"name": "system"
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},
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{
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"label": "Assistant",
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"name": "assistant"
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},
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{
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"label": "Developer",
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"name": "developer"
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},
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{
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"label": "User",
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"name": "user"
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}
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]
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},
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{
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"label": "Content",
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"name": "content",
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"type": "string",
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"acceptVariable": true,
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"generateInstruction": true,
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"rows": 4
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}
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],
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"id": "agentAgentflow_0-input-agentMessages-array",
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"display": true
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},
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{
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"label": "Tools",
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"name": "agentTools",
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"type": "array",
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"optional": true,
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"array": [
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{
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"label": "Tool",
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"name": "agentSelectedTool",
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"type": "asyncOptions",
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"loadMethod": "listTools",
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"loadConfig": true
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||||
},
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{
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"label": "Require Human Input",
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"name": "agentSelectedToolRequiresHumanInput",
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"type": "boolean",
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"optional": true
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}
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],
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"id": "agentAgentflow_0-input-agentTools-array",
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"display": true
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},
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{
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"label": "Knowledge (Document Stores)",
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"name": "agentKnowledgeDocumentStores",
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"type": "array",
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"description": "Give your agent context about different document sources. Document stores must be upserted in advance.",
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"array": [
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{
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"label": "Document Store",
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"name": "documentStore",
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"type": "asyncOptions",
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"loadMethod": "listStores"
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},
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{
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"label": "Describe Knowledge",
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"name": "docStoreDescription",
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"type": "string",
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"generateDocStoreDescription": true,
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"placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
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"rows": 4
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},
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{
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"label": "Return Source Documents",
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"name": "returnSourceDocuments",
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"type": "boolean",
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"optional": true
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}
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],
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"optional": true,
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"id": "agentAgentflow_0-input-agentKnowledgeDocumentStores-array",
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"display": true
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},
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{
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"label": "Knowledge (Vector Embeddings)",
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"name": "agentKnowledgeVSEmbeddings",
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"type": "array",
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"description": "Give your agent context about different document sources from existing vector stores and embeddings",
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"array": [
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{
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"label": "Vector Store",
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"name": "vectorStore",
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"type": "asyncOptions",
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"loadMethod": "listVectorStores",
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"loadConfig": true
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},
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{
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"label": "Embedding Model",
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"name": "embeddingModel",
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"type": "asyncOptions",
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"loadMethod": "listEmbeddings",
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"loadConfig": true
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},
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{
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"label": "Knowledge Name",
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"name": "knowledgeName",
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"type": "string",
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"placeholder": "A short name for the knowledge base, this is useful for the AI to know when and how to search for correct information"
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},
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{
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"label": "Describe Knowledge",
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"name": "knowledgeDescription",
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"type": "string",
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"placeholder": "Describe what the knowledge base is about, this is useful for the AI to know when and how to search for correct information",
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"rows": 4
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},
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{
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"label": "Return Source Documents",
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"name": "returnSourceDocuments",
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"type": "boolean",
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||||
"optional": true
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||||
}
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],
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"optional": true,
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"id": "agentAgentflow_0-input-agentKnowledgeVSEmbeddings-array",
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"display": true
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||||
},
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{
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"label": "Enable Memory",
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"name": "agentEnableMemory",
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"type": "boolean",
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"description": "Enable memory for the conversation thread",
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"default": true,
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"optional": true,
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"id": "agentAgentflow_0-input-agentEnableMemory-boolean",
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||||
"display": true
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||||
},
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||||
{
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||||
"label": "Memory Type",
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"name": "agentMemoryType",
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"type": "options",
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"options": [
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{
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"label": "All Messages",
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"name": "allMessages",
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"description": "Retrieve all messages from the conversation"
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},
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{
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"label": "Window Size",
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"name": "windowSize",
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"description": "Uses a fixed window size to surface the last N messages"
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},
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{
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"label": "Conversation Summary",
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"name": "conversationSummary",
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"description": "Summarizes the whole conversation"
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},
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{
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"label": "Conversation Summary Buffer",
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"name": "conversationSummaryBuffer",
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"description": "Summarize conversations once token limit is reached. Default to 2000"
|
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}
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],
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"optional": true,
|
||||
"default": "allMessages",
|
||||
"show": {
|
||||
"agentEnableMemory": true
|
||||
},
|
||||
"id": "agentAgentflow_0-input-agentMemoryType-options",
|
||||
"display": true
|
||||
},
|
||||
{
|
||||
"label": "Window Size",
|
||||
"name": "agentMemoryWindowSize",
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||||
"type": "number",
|
||||
"default": "20",
|
||||
"description": "Uses a fixed window size to surface the last N messages",
|
||||
"show": {
|
||||
"agentMemoryType": "windowSize"
|
||||
},
|
||||
"id": "agentAgentflow_0-input-agentMemoryWindowSize-number",
|
||||
"display": false
|
||||
},
|
||||
{
|
||||
"label": "Max Token Limit",
|
||||
"name": "agentMemoryMaxTokenLimit",
|
||||
"type": "number",
|
||||
"default": "2000",
|
||||
"description": "Summarize conversations once token limit is reached. Default to 2000",
|
||||
"show": {
|
||||
"agentMemoryType": "conversationSummaryBuffer"
|
||||
},
|
||||
"id": "agentAgentflow_0-input-agentMemoryMaxTokenLimit-number",
|
||||
"display": false
|
||||
},
|
||||
{
|
||||
"label": "Input Message",
|
||||
"name": "agentUserMessage",
|
||||
"type": "string",
|
||||
"description": "Add an input message as user message at the end of the conversation",
|
||||
"rows": 4,
|
||||
"optional": true,
|
||||
"acceptVariable": true,
|
||||
"show": {
|
||||
"agentEnableMemory": true
|
||||
},
|
||||
"id": "agentAgentflow_0-input-agentUserMessage-string",
|
||||
"display": true
|
||||
},
|
||||
{
|
||||
"label": "Return Response As",
|
||||
"name": "agentReturnResponseAs",
|
||||
"type": "options",
|
||||
"options": [
|
||||
{
|
||||
"label": "User Message",
|
||||
"name": "userMessage"
|
||||
},
|
||||
{
|
||||
"label": "Assistant Message",
|
||||
"name": "assistantMessage"
|
||||
}
|
||||
],
|
||||
"default": "userMessage",
|
||||
"id": "agentAgentflow_0-input-agentReturnResponseAs-options",
|
||||
"display": true
|
||||
},
|
||||
{
|
||||
"label": "Update Flow State",
|
||||
"name": "agentUpdateState",
|
||||
"description": "Update runtime state during the execution of the workflow",
|
||||
"type": "array",
|
||||
"optional": true,
|
||||
"acceptVariable": true,
|
||||
"array": [
|
||||
{
|
||||
"label": "Key",
|
||||
"name": "key",
|
||||
"type": "asyncOptions",
|
||||
"loadMethod": "listRuntimeStateKeys",
|
||||
"freeSolo": true
|
||||
},
|
||||
{
|
||||
"label": "Value",
|
||||
"name": "value",
|
||||
"type": "string",
|
||||
"acceptVariable": true,
|
||||
"acceptNodeOutputAsVariable": true
|
||||
}
|
||||
],
|
||||
"id": "agentAgentflow_0-input-agentUpdateState-array",
|
||||
"display": true
|
||||
}
|
||||
],
|
||||
"inputAnchors": [],
|
||||
"inputs": {
|
||||
"agentModel": "chatOpenAI",
|
||||
"agentMessages": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": "<p>You are a helpful assistant. Using the provided context, answer the user's question to the best of your ability using the resources provided.</p><p>If there is nothing in the context relevant to the question at hand, just say \"Hmm, I'm not sure.\" Don't try to make up an answer.</p>"
|
||||
}
|
||||
],
|
||||
"agentTools": "",
|
||||
"agentKnowledgeDocumentStores": [
|
||||
{
|
||||
"documentStore": "25429b8f-0377-4762-9cda-0d5366cf022c:AI-Paper",
|
||||
"docStoreDescription": "This paper provides an extensive overview of artificial intelligence-generated content (AIGC), including its definition, capabilities, applications, challenges, and future directions, serving as a valuable resource for researchers and industry professionals to understand and harness AIGC's potential.",
|
||||
"returnSourceDocuments": true
|
||||
}
|
||||
],
|
||||
"agentKnowledgeVSEmbeddings": "",
|
||||
"agentEnableMemory": true,
|
||||
"agentMemoryType": "allMessages",
|
||||
"agentUserMessage": "",
|
||||
"agentReturnResponseAs": "userMessage",
|
||||
"agentUpdateState": "",
|
||||
"agentModelConfig": {
|
||||
"cache": "",
|
||||
"modelName": "gpt-4o-mini",
|
||||
"temperature": 0.9,
|
||||
"streaming": true,
|
||||
"maxTokens": "",
|
||||
"topP": "",
|
||||
"frequencyPenalty": "",
|
||||
"presencePenalty": "",
|
||||
"timeout": "",
|
||||
"strictToolCalling": "",
|
||||
"stopSequence": "",
|
||||
"basepath": "",
|
||||
"proxyUrl": "",
|
||||
"baseOptions": "",
|
||||
"allowImageUploads": "",
|
||||
"imageResolution": "low",
|
||||
"reasoningEffort": "medium",
|
||||
"agentModel": "chatOpenAI"
|
||||
}
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "agentAgentflow_0-output-agentAgentflow",
|
||||
"label": "Agent",
|
||||
"name": "agentAgentflow"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"type": "agentFlow",
|
||||
"width": 175,
|
||||
"height": 72,
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 216.75,
|
||||
"y": 96.5
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"id": "stickyNoteAgentflow_0",
|
||||
"position": {
|
||||
"x": 209.875,
|
||||
"y": -61.25
|
||||
},
|
||||
"data": {
|
||||
"id": "stickyNoteAgentflow_0",
|
||||
"label": "Sticky Note",
|
||||
"version": 1,
|
||||
"name": "stickyNoteAgentflow",
|
||||
"type": "StickyNote",
|
||||
"color": "#fee440",
|
||||
"baseClasses": ["StickyNote"],
|
||||
"category": "Agent Flows",
|
||||
"description": "Add notes to the agent flow",
|
||||
"inputParams": [
|
||||
{
|
||||
"label": "",
|
||||
"name": "note",
|
||||
"type": "string",
|
||||
"rows": 1,
|
||||
"placeholder": "Type something here",
|
||||
"optional": true,
|
||||
"id": "stickyNoteAgentflow_0-input-note-string",
|
||||
"display": true
|
||||
}
|
||||
],
|
||||
"inputAnchors": [],
|
||||
"inputs": {
|
||||
"note": "Agent can retrieve documents from upserted document store, and directly from vector database"
|
||||
},
|
||||
"outputAnchors": [
|
||||
{
|
||||
"id": "stickyNoteAgentflow_0-output-stickyNoteAgentflow",
|
||||
"label": "Sticky Note",
|
||||
"name": "stickyNoteAgentflow"
|
||||
}
|
||||
],
|
||||
"outputs": {},
|
||||
"selected": false
|
||||
},
|
||||
"type": "stickyNote",
|
||||
"width": 210,
|
||||
"height": 143,
|
||||
"selected": false,
|
||||
"positionAbsolute": {
|
||||
"x": 209.875,
|
||||
"y": -61.25
|
||||
},
|
||||
"dragging": false
|
||||
}
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"source": "startAgentflow_0",
|
||||
"sourceHandle": "startAgentflow_0-output-startAgentflow",
|
||||
"target": "agentAgentflow_0",
|
||||
"targetHandle": "agentAgentflow_0",
|
||||
"data": {
|
||||
"sourceColor": "#7EE787",
|
||||
"targetColor": "#4DD0E1",
|
||||
"isHumanInput": false
|
||||
},
|
||||
"type": "agentFlow",
|
||||
"id": "startAgentflow_0-startAgentflow_0-output-startAgentflow-agentAgentflow_0-agentAgentflow_0"
|
||||
}
|
||||
]
|
||||
}
|
||||
Reference in New Issue
Block a user