mirror of
https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-28 21:00:58 +03:00
Henry Heng
7924fbce0d
* agent flow v2 * chat message background * conditon agent flow * add sticky note * update human input dynamic prompt * add HTTP node * add default tool icon * fix export duplicate agentflow v2 * add agentflow v2 marketplaces * refractor memoization, add iteration nodes * add agentflow v2 templates * add agentflow generator * add migration scripts for mysql, mariadb, posrgres and fix date filters for executions * update agentflow chat history config * fix get all flows error after deletion and rename * add previous nodes from parent node * update generator prompt * update run time state when using iteration nodes * prevent looping connection, prevent duplication of start node, add executeflow node, add nodes agentflow, chat history variable * update embed * convert form input to string * bump openai version * add react rewards * add prompt generator to prediction queue * add array schema to overrideconfig * UI touchup * update embedded chat version * fix node info dialog * update start node and loop default iteration * update UI fixes for agentflow v2 * fix async drop down * add export import to agentflowsv2, executions, fix UI bugs * add default empty object to flowlisttable * add ability to share trace link publicly, allow MCP tool use for Agent and Assistant * add runtime message length to variable, display conditions on UI * fix array validation * add ability to add knowledge from vector store and embeddings for agent * add agent tool require human input * add ephemeral memory to start node * update agent flow node to show vs and embeddings icons * feat: add import chat data functionality for AgentFlowV2 * feat: set chatMessage.executionId to null if not found in import JSON file or database * fix: MariaDB execution migration script to utf8mb4_unicode_520_ci --------- Co-authored-by: Ong Chung Yau <33013947+chungyau97@users.noreply.github.com> Co-authored-by: chungyau97 <chungyau97@gmail.com>
978 lines
44 KiB
JSON
978 lines
44 KiB
JSON
{
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"description": "Customer support team consisting of Support Representative and Quality Assurance Specialist to handle support tickets",
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"framework": ["Langchain"],
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"usecases": ["Customer Support", "Hierarchical Agent Teams"],
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"nodes": [
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{
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"id": "supervisor_0",
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"position": {
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"x": 343.59847938459717,
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"y": 124.00657409829381
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},
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"type": "customNode",
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"data": {
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"id": "supervisor_0",
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"label": "Supervisor",
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"version": 1,
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"name": "supervisor",
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"type": "Supervisor",
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"baseClasses": ["Supervisor"],
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"category": "Multi Agents",
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"inputParams": [
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{
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"label": "Supervisor Name",
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"name": "supervisorName",
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"type": "string",
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"placeholder": "Supervisor",
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"default": "Supervisor",
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"id": "supervisor_0-input-supervisorName-string"
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},
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{
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"label": "Supervisor Prompt",
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"name": "supervisorPrompt",
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"type": "string",
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"description": "Prompt must contains {team_members}",
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"rows": 4,
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"default": "You are a supervisor tasked with managing a conversation between the following workers: {team_members}.\nGiven the following user request, respond with the worker to act next.\nEach worker will perform a task and respond with their results and status.\nWhen finished, respond with FINISH.\nSelect strategically to minimize the number of steps taken.",
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"additionalParams": true,
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"id": "supervisor_0-input-supervisorPrompt-string"
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},
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{
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"label": "Recursion Limit",
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"name": "recursionLimit",
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"type": "number",
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"description": "Maximum number of times a call can recurse. If not provided, defaults to 100.",
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"default": 100,
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"additionalParams": true,
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"id": "supervisor_0-input-recursionLimit-number"
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}
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],
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"inputAnchors": [
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{
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"label": "Tool Calling Chat Model",
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"name": "model",
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"type": "BaseChatModel",
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"description": "Only compatible with models that are capable of function calling: ChatOpenAI, ChatMistral, ChatAnthropic, ChatGoogleGenerativeAI, GroqChat. Best result with GPT-4 model",
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"id": "supervisor_0-input-model-BaseChatModel"
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},
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{
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"label": "Input Moderation",
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"description": "Detect text that could generate harmful output and prevent it from being sent to the language model",
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"name": "inputModeration",
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"type": "Moderation",
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"optional": true,
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"list": true,
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"id": "supervisor_0-input-inputModeration-Moderation"
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}
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],
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"inputs": {
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"supervisorName": "Supervisor",
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"supervisorPrompt": "You are a supervisor tasked with managing a conversation between the following workers: {team_members}.\nGiven the following user request, respond with the worker to act next.\nEach worker will perform a task and respond with their results and status.\nWhen finished, respond with FINISH.\nSelect strategically to minimize the number of steps taken.",
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"model": "{{chatOpenAI_0.data.instance}}",
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"recursionLimit": 100,
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"inputModeration": ""
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},
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"outputAnchors": [
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{
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"id": "supervisor_0-output-supervisor-Supervisor",
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"name": "supervisor",
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"label": "Supervisor",
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"description": "",
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"type": "Supervisor"
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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": 300,
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"height": 431,
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"selected": false,
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"positionAbsolute": {
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"x": 343.59847938459717,
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"y": 124.00657409829381
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},
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"dragging": false
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},
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{
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"id": "worker_0",
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"position": {
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"x": 848.0791314419789,
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"y": 550.1251435439353
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},
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"type": "customNode",
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"data": {
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"id": "worker_0",
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"label": "Worker",
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"version": 1,
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"name": "worker",
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"type": "Worker",
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"baseClasses": ["Worker"],
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"category": "Multi Agents",
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"inputParams": [
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{
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"label": "Worker Name",
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"name": "workerName",
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"type": "string",
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"placeholder": "Worker",
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"id": "worker_0-input-workerName-string"
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},
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{
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"label": "Worker Prompt",
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"name": "workerPrompt",
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"type": "string",
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"rows": 4,
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"default": "You are a research assistant who can search for up-to-date info using search engine.",
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"id": "worker_0-input-workerPrompt-string"
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},
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{
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"label": "Format Prompt Values",
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"name": "promptValues",
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"type": "json",
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"optional": true,
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"acceptVariable": true,
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"list": true,
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"id": "worker_0-input-promptValues-json"
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},
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{
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"label": "Max Iterations",
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"name": "maxIterations",
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"type": "number",
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"optional": true,
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"id": "worker_0-input-maxIterations-number"
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}
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],
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"inputAnchors": [
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{
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"label": "Tools",
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"name": "tools",
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"type": "Tool",
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"list": true,
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"optional": true,
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"id": "worker_0-input-tools-Tool"
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},
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{
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"label": "Supervisor",
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"name": "supervisor",
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"type": "Supervisor",
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"id": "worker_0-input-supervisor-Supervisor"
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},
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{
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"label": "Tool Calling Chat Model",
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"name": "model",
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"type": "BaseChatModel",
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"optional": true,
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"description": "Only compatible with models that are capable of function calling: ChatOpenAI, ChatMistral, ChatAnthropic, ChatGoogleGenerativeAI, ChatVertexAI, GroqChat. If not specified, supervisor's model will be used",
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"id": "worker_0-input-model-BaseChatModel"
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}
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],
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"inputs": {
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"workerName": "Quality Assurance Specialist",
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"workerPrompt": "You are working at {company} and are now collaborating with your team on a customer request. Your task is to ensure that the support representative delivers the best possible support. It's crucial that the representative provides complete, accurate answers without making any assumptions.\n\nYour objective is to maintain top-tier support quality assurance within your team.\n\nReview the response drafted by the support representative for the customer's inquiry. Make sure the answer is thorough, accurate, and meets the high standards expected in customer support. Confirm that every aspect of the customer's question is addressed comprehensively, with a friendly and helpful tone. Verify that all references and sources used to find the information are included, ensuring the response is well-supported and leaves no questions unanswered.\n\nOnce your review is complete, return it to the Support Representative for finalization.",
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"tools": "",
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"supervisor": "{{supervisor_0.data.instance}}",
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"model": "",
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"promptValues": "{\"company\":\"Flowise Inc\"}",
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"maxIterations": ""
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},
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"outputAnchors": [
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{
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"id": "worker_0-output-worker-Worker",
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"name": "worker",
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"label": "Worker",
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"description": "",
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"type": "Worker"
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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": 300,
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"height": 808,
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"positionAbsolute": {
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"x": 848.0791314419789,
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"y": 550.1251435439353
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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": "worker_1",
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"position": {
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"x": 1573.2919579833303,
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"y": -234.22598124451474
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},
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"type": "customNode",
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"data": {
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"id": "worker_1",
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"label": "Worker",
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"version": 1,
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"name": "worker",
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"type": "Worker",
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"baseClasses": ["Worker"],
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"category": "Multi Agents",
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"inputParams": [
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{
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"label": "Worker Name",
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"name": "workerName",
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"type": "string",
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"placeholder": "Worker",
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"id": "worker_1-input-workerName-string"
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},
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{
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"label": "Worker Prompt",
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"name": "workerPrompt",
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"type": "string",
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"rows": 4,
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"default": "You are a research assistant who can search for up-to-date info using search engine.",
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"id": "worker_1-input-workerPrompt-string"
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},
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{
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"label": "Format Prompt Values",
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"name": "promptValues",
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"type": "json",
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"optional": true,
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"acceptVariable": true,
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"list": true,
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"id": "worker_1-input-promptValues-json"
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},
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{
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"label": "Max Iterations",
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"name": "maxIterations",
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"type": "number",
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"optional": true,
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"id": "worker_1-input-maxIterations-number"
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}
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],
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"inputAnchors": [
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{
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"label": "Tools",
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"name": "tools",
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"type": "Tool",
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"list": true,
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"optional": true,
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"id": "worker_1-input-tools-Tool"
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},
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{
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"label": "Supervisor",
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"name": "supervisor",
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"type": "Supervisor",
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"id": "worker_1-input-supervisor-Supervisor"
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},
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{
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"label": "Tool Calling Chat Model",
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"name": "model",
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"type": "BaseChatModel",
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"optional": true,
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"description": "Only compatible with models that are capable of function calling: ChatOpenAI, ChatMistral, ChatAnthropic, ChatGoogleGenerativeAI, ChatVertexAI, GroqChat. If not specified, supervisor's model will be used",
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"id": "worker_1-input-model-BaseChatModel"
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}
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],
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"inputs": {
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"workerName": "Support Representative",
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"workerPrompt": "As a representative at {company}, your role is to deliver exceptional customer support. Your objective is to provide the highest quality assistance, ensuring that your answers are comprehensive and based on facts without any assumptions.\n\nYour goal is to strive to be the most friendly and helpful support representative on your team.\n\nHere is your previous conversation with the customer:\n{conversation}\n\nCraft a detailed and informative response to the customer's inquiry, addressing all aspects of their question. Your response should include references to all sources used to find the answer, including external data or solutions. Ensure your answer is thorough, leaving no questions unanswered, while maintaining a friendly and supportive tone throughout.\n\nAlways use the tool provided - search_docs to look for answers. Check if you need to pass the result to Quality Assurance Specialist for review.",
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"tools": ["{{retrieverTool_0.data.instance}}"],
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"supervisor": "{{supervisor_0.data.instance}}",
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"model": "",
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"promptValues": "{\"company\":\"Flowise Inc\",\"conversation\":\"{{customFunction_0.data.instance}}\"}",
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"maxIterations": ""
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},
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"outputAnchors": [
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{
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"id": "worker_1-output-worker-Worker",
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"name": "worker",
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"label": "Worker",
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"description": "",
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"type": "Worker"
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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": 300,
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"height": 808,
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"positionAbsolute": {
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"x": 1573.2919579833303,
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"y": -234.22598124451474
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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": "retrieverTool_0",
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"position": {
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"x": 1136.3773214513722,
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"y": -661.7020929797668
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},
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"type": "customNode",
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"data": {
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"id": "retrieverTool_0",
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"label": "Retriever Tool",
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"version": 2,
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"name": "retrieverTool",
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"type": "RetrieverTool",
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"baseClasses": ["RetrieverTool", "DynamicTool", "Tool", "StructuredTool", "Runnable"],
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"category": "Tools",
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"description": "Use a retriever as allowed tool for agent",
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"inputParams": [
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{
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"label": "Retriever Name",
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"name": "name",
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"type": "string",
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"placeholder": "search_state_of_union",
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"id": "retrieverTool_0-input-name-string"
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},
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{
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"label": "Retriever Description",
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"name": "description",
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"type": "string",
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"description": "When should agent uses to retrieve documents",
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"rows": 3,
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"placeholder": "Searches and returns documents regarding the state-of-the-union.",
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"id": "retrieverTool_0-input-description-string"
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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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"id": "retrieverTool_0-input-returnSourceDocuments-boolean"
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}
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],
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"inputAnchors": [
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{
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"label": "Retriever",
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"name": "retriever",
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"type": "BaseRetriever",
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"id": "retrieverTool_0-input-retriever-BaseRetriever"
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}
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],
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"inputs": {
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"name": "search_docs",
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"description": "Search and return documents about any issue or bugfix. Always give priority to this tool",
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"retriever": "{{pinecone_0.data.instance}}",
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"returnSourceDocuments": ""
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},
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"outputAnchors": [
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{
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"id": "retrieverTool_0-output-retrieverTool-RetrieverTool|DynamicTool|Tool|StructuredTool|Runnable",
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"name": "retrieverTool",
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"label": "RetrieverTool",
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"description": "Use a retriever as allowed tool for agent",
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"type": "RetrieverTool | DynamicTool | Tool | StructuredTool | Runnable"
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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": 300,
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"height": 602,
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"selected": false,
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"positionAbsolute": {
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"x": 1136.3773214513722,
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"y": -661.7020929797668
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},
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"dragging": false
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},
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{
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"id": "pinecone_0",
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"position": {
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"x": 767.1744633865214,
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"y": -634.6870559540365
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},
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"type": "customNode",
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"data": {
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"id": "pinecone_0",
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"label": "Pinecone",
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"version": 3,
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"name": "pinecone",
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"type": "Pinecone",
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"baseClasses": ["Pinecone", "VectorStoreRetriever", "BaseRetriever"],
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"category": "Vector Stores",
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"description": "Upsert embedded data and perform similarity or mmr search using Pinecone, a leading fully managed hosted vector database",
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"inputParams": [
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{
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"label": "Connect Credential",
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"name": "credential",
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"type": "credential",
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"credentialNames": ["pineconeApi"],
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"id": "pinecone_0-input-credential-credential"
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},
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{
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"label": "Pinecone Index",
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"name": "pineconeIndex",
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"type": "string",
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"id": "pinecone_0-input-pineconeIndex-string"
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},
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{
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"label": "Pinecone Namespace",
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"name": "pineconeNamespace",
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"type": "string",
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"placeholder": "my-first-namespace",
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"additionalParams": true,
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"optional": true,
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"id": "pinecone_0-input-pineconeNamespace-string"
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},
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{
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"label": "Pinecone Metadata Filter",
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"name": "pineconeMetadataFilter",
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"type": "json",
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"optional": true,
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"additionalParams": true,
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"id": "pinecone_0-input-pineconeMetadataFilter-json"
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},
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{
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"label": "Top K",
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"name": "topK",
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"description": "Number of top results to fetch. Default to 4",
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"placeholder": "4",
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"type": "number",
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"additionalParams": true,
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"optional": true,
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"id": "pinecone_0-input-topK-number"
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},
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{
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"label": "Search Type",
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"name": "searchType",
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"type": "options",
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"default": "similarity",
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"options": [
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{
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"label": "Similarity",
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"name": "similarity"
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},
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{
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"label": "Max Marginal Relevance",
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"name": "mmr"
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}
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],
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"additionalParams": true,
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"optional": true,
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"id": "pinecone_0-input-searchType-options"
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},
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{
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"label": "Fetch K (for MMR Search)",
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"name": "fetchK",
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"description": "Number of initial documents to fetch for MMR reranking. Default to 20. Used only when the search type is MMR",
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"placeholder": "20",
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"type": "number",
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"additionalParams": true,
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"optional": true,
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"id": "pinecone_0-input-fetchK-number"
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|
},
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{
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|
"label": "Lambda (for MMR Search)",
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|
"name": "lambda",
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|
"description": "Number between 0 and 1 that determines the degree of diversity among the results, where 0 corresponds to maximum diversity and 1 to minimum diversity. Used only when the search type is MMR",
|
|
"placeholder": "0.5",
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"type": "number",
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"additionalParams": true,
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|
"optional": true,
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|
"id": "pinecone_0-input-lambda-number"
|
|
}
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|
],
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"inputAnchors": [
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{
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