mirror of
https://github.com/farcasclaudiu/Flowise.git
synced 2026-06-22 09:01:09 +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>
460 lines
22 KiB
JSON
460 lines
22 KiB
JSON
{
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"description": "Given API docs, agent automatically decide which API to call, generating url and body request from conversation",
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"framework": ["Langchain"],
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"usecases": ["Interacting with API"],
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"nodes": [
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{
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"id": "toolAgent_0",
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"position": {
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"x": 2142.702888476286,
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"y": 52.064582962824204
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},
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"type": "customNode",
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"data": {
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"id": "toolAgent_0",
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"label": "Tool Agent",
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"version": 2,
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"name": "toolAgent",
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"type": "AgentExecutor",
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"baseClasses": ["AgentExecutor", "BaseChain", "Runnable"],
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"category": "Agents",
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"description": "Agent that uses Function Calling to pick the tools and args to call",
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"inputParams": [
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{
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"label": "System Message",
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"name": "systemMessage",
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"type": "string",
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"default": "You are a helpful AI assistant.",
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"description": "If Chat Prompt Template is provided, this will be ignored",
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"rows": 4,
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"optional": true,
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"additionalParams": true,
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"id": "toolAgent_0-input-systemMessage-string"
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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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"additionalParams": true,
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"id": "toolAgent_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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"id": "toolAgent_0-input-tools-Tool"
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},
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{
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"label": "Memory",
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"name": "memory",
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"type": "BaseChatMemory",
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"id": "toolAgent_0-input-memory-BaseChatMemory"
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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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"description": "Only compatible with models that are capable of function calling: ChatOpenAI, ChatMistral, ChatAnthropic, ChatGoogleGenerativeAI, ChatVertexAI, GroqChat",
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"id": "toolAgent_0-input-model-BaseChatModel"
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},
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{
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"label": "Chat Prompt Template",
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"name": "chatPromptTemplate",
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"type": "ChatPromptTemplate",
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"description": "Override existing prompt with Chat Prompt Template. Human Message must includes {input} variable",
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"optional": true,
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"id": "toolAgent_0-input-chatPromptTemplate-ChatPromptTemplate"
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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": "toolAgent_0-input-inputModeration-Moderation"
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}
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],
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"inputs": {
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"tools": ["{{openAPIToolkit_0.data.instance}}"],
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"memory": "{{bufferMemory_0.data.instance}}",
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"model": "{{chatAnthropic_0.data.instance}}",
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"chatPromptTemplate": "",
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"systemMessage": "You are an agent that can interact with the API to perform specific tasks based on user requests.\n\nYour main goal is to understand the user's needs, make appropriate API calls, and return the results in a clear format. Ensure you verify inputs before making API requests and handle errors gracefully if the API fails.\n\n# Steps\n\n1. **Receive User Input:** Listen carefully to the user's request and identify key parameters needed for the API call.\n2. **Validate Input:** Ensure that the user input is in the correct format and contains all necessary information.\n3. **Make API Call:** Use the provided OpenAPI tools to call appropriate API endpoint with the validated input.\n",
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"inputModeration": "",
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"maxIterations": ""
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},
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"outputAnchors": [
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{
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"id": "toolAgent_0-output-toolAgent-AgentExecutor|BaseChain|Runnable",
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"name": "toolAgent",
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"label": "AgentExecutor",
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"description": "Agent that uses Function Calling to pick the tools and args to call",
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"type": "AgentExecutor | BaseChain | 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": 483,
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"selected": false,
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"positionAbsolute": {
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"x": 2142.702888476286,
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"y": 52.064582962824204
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},
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"dragging": false
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},
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{
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"id": "bufferMemory_0",
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"position": {
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"x": 1017.5366991719394,
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"y": 70.40237946649512
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},
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"type": "customNode",
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"data": {
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"id": "bufferMemory_0",
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"label": "Buffer Memory",
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"version": 2,
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"name": "bufferMemory",
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"type": "BufferMemory",
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"baseClasses": ["BufferMemory", "BaseChatMemory", "BaseMemory"],
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"category": "Memory",
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"description": "Retrieve chat messages stored in database",
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"inputParams": [
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{
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"label": "Session Id",
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"name": "sessionId",
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"type": "string",
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"description": "If not specified, a random id will be used. Learn <a target=\"_blank\" href=\"https://docs.flowiseai.com/memory#ui-and-embedded-chat\">more</a>",
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"default": "",
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"additionalParams": true,
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"optional": true,
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"id": "bufferMemory_0-input-sessionId-string"
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},
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{
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"label": "Memory Key",
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"name": "memoryKey",
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"type": "string",
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"default": "chat_history",
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"additionalParams": true,
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"id": "bufferMemory_0-input-memoryKey-string"
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}
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],
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"inputAnchors": [],
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"inputs": {
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"sessionId": "",
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"memoryKey": "chat_history"
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},
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"outputAnchors": [
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{
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"id": "bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory",
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"name": "bufferMemory",
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"label": "BufferMemory",
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"description": "Retrieve chat messages stored in database",
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"type": "BufferMemory | BaseChatMemory | BaseMemory"
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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": 250,
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"selected": false,
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"positionAbsolute": {
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"x": 1017.5366991719394,
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"y": 70.40237946649512
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},
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"dragging": false
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},
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{
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"id": "chatAnthropic_0",
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"position": {
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"x": 1782.2489802995697,
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"y": -97.03292069533617
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},
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"type": "customNode",
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"data": {
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"id": "chatAnthropic_0",
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"label": "ChatAnthropic",
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"version": 8,
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"name": "chatAnthropic",
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"type": "ChatAnthropic",
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"baseClasses": ["ChatAnthropic", "ChatAnthropicMessages", "BaseChatModel", "BaseLanguageModel", "Runnable"],
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"category": "Chat Models",
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"description": "Wrapper around ChatAnthropic large language models that use the Chat endpoint",
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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": ["anthropicApi"],
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"id": "chatAnthropic_0-input-credential-credential",
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"display": true
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},
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{
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"label": "Model Name",
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"name": "modelName",
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"type": "asyncOptions",
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"loadMethod": "listModels",
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"default": "claude-3-haiku",
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"id": "chatAnthropic_0-input-modelName-asyncOptions",
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"display": true
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},
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{
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"label": "Temperature",
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"name": "temperature",
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"type": "number",
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"step": 0.1,
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"default": 0.9,
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"optional": true,
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"id": "chatAnthropic_0-input-temperature-number",
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"display": true
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},
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{
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"label": "Streaming",
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"name": "streaming",
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"type": "boolean",
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"default": true,
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"optional": true,
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"additionalParams": true,
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"id": "chatAnthropic_0-input-streaming-boolean",
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"display": true
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},
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{
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"label": "Max Tokens",
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"name": "maxTokensToSample",
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"type": "number",
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"step": 1,
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"optional": true,
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"additionalParams": true,
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"id": "chatAnthropic_0-input-maxTokensToSample-number",
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"display": true
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},
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{
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"label": "Top P",
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"name": "topP",
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"type": "number",
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"step": 0.1,
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"optional": true,
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"additionalParams": true,
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"id": "chatAnthropic_0-input-topP-number",
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"display": true
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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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"type": "number",
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"step": 0.1,
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"optional": true,
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"additionalParams": true,
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"id": "chatAnthropic_0-input-topK-number",
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"display": true
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},
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{
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"label": "Extended Thinking",
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"name": "extendedThinking",
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"type": "boolean",
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"description": "Enable extended thinking for reasoning model such as Claude Sonnet 3.7",
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"optional": true,
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"additionalParams": true,
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"id": "chatAnthropic_0-input-extendedThinking-boolean",
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"display": true
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},
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{
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"label": "Budget Tokens",
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"name": "budgetTokens",
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"type": "number",
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"step": 1,
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"default": 1024,
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"description": "Maximum number of tokens Claude is allowed use for its internal reasoning process",
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"optional": true,
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"additionalParams": true,
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"id": "chatAnthropic_0-input-budgetTokens-number",
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"display": true
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},
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{
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"label": "Allow Image Uploads",
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"name": "allowImageUploads",
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"type": "boolean",
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"description": "Allow image input. Refer to the <a href=\"https://docs.flowiseai.com/using-flowise/uploads#image\" target=\"_blank\">docs</a> for more details.",
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"default": false,
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"optional": true,
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"id": "chatAnthropic_0-input-allowImageUploads-boolean",
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"display": true
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}
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],
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"inputAnchors": [
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{
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"label": "Cache",
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"name": "cache",
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"type": "BaseCache",
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"optional": true,
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"id": "chatAnthropic_0-input-cache-BaseCache",
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"display": true
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}
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],
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"inputs": {
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"cache": "",
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"modelName": "claude-3-5-haiku-latest",
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"temperature": 0.9,
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"streaming": true,
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"maxTokensToSample": "",
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"topP": "",
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"topK": "",
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"extendedThinking": "",
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"budgetTokens": 1024,
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"allowImageUploads": ""
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},
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"outputAnchors": [
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{
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"id": "chatAnthropic_0-output-chatAnthropic-ChatAnthropic|ChatAnthropicMessages|BaseChatModel|BaseLanguageModel|Runnable",
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"name": "chatAnthropic",
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"label": "ChatAnthropic",
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"description": "Wrapper around ChatAnthropic large language models that use the Chat endpoint",
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"type": "ChatAnthropic | ChatAnthropicMessages | BaseChatModel | BaseLanguageModel | 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": 668,
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"selected": false,
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"positionAbsolute": {
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"x": 1782.2489802995697,
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"y": -97.03292069533617
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},
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"dragging": false
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},
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{
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"id": "openAPIToolkit_0",
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"position": {
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"x": 1406.3474125716532,
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"y": -26.543208700976493
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},
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"type": "customNode",
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"data": {
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"id": "openAPIToolkit_0",
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"label": "OpenAPI Toolkit",
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"version": 2,
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"name": "openAPIToolkit",
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"type": "OpenAPIToolkit",
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"baseClasses": ["OpenAPIToolkit", "Tool"],
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"category": "Tools",
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"description": "Load OpenAPI specification, and converts each API endpoint to a tool",
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"inputParams": [
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{
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"label": "YAML File",
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"name": "yamlFile",
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"type": "file",
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"fileType": ".yaml",
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"id": "openAPIToolkit_0-input-yamlFile-file",
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"display": true
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},
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{
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"label": "Return Direct",
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"name": "returnDirect",
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"description": "Return the output of the tool directly to the user",
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"type": "boolean",
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"optional": true,
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"id": "openAPIToolkit_0-input-returnDirect-boolean",
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"display": true
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},
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{
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"label": "Headers",
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"name": "headers",
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"type": "json",
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"description": "Request headers to be sent with the API request. For example, {\"Authorization\": \"Bearer token\"}",
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"additionalParams": true,
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"optional": true,
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"id": "openAPIToolkit_0-input-headers-json",
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"display": true
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},
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{
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"label": "Remove null parameters",
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"name": "removeNulls",
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"type": "boolean",
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"optional": true,
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"description": "Remove all keys with null values from the parsed arguments",
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"id": "openAPIToolkit_0-input-removeNulls-boolean",
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"display": true
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},
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{
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"label": "Custom Code",
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"name": "customCode",
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"type": "code",
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"hint": {
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"label": "How to use",
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"value": "- **Libraries:** \n You can use any libraries imported in Flowise.\n\n- **Tool Input Arguments:** \n Tool input arguments are available as the following variables:\n - `$PathParameters`\n - `$QueryParameters`\n - `$RequestBody`\n\n- **HTTP Requests:** \n By default, you can get the following values for making HTTP requests:\n - `$url`\n - `$options`\n\n- **Default Flow Config:** \n You can access the default flow configuration using these variables:\n - `$flow.sessionId`\n - `$flow.chatId`\n - `$flow.chatflowId`\n - `$flow.input`\n - `$flow.state`\n\n- **Custom Variables:** \n You can get custom variables using the syntax:\n - `$vars.<variable-name>`\n\n- **Return Value:** \n The function must return a **string** value at the end.\n\n```js\nconst fetch = require('node-fetch');\nconst url = $url;\nconst options = $options;\n\ntry {\n\tconst response = await fetch(url, options);\n\tconst resp = await response.json();\n\treturn JSON.stringify(resp);\n} catch (error) {\n\tconsole.error(error);\n\treturn '';\n}\n\n```\n"
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},
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"codeExample": "const fetch = require('node-fetch');\nconst url = $url;\nconst options = $options;\n\ntry {\n\tconst response = await fetch(url, options);\n\tconst resp = await response.json();\n\treturn JSON.stringify(resp);\n} catch (error) {\n\tconsole.error(error);\n\treturn '';\n}\n",
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"description": "Custom code to return the output of the tool. The code should be a function that takes in the input and returns a string",
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"hideCodeExecute": true,
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"default": "const fetch = require('node-fetch');\nconst url = $url;\nconst options = $options;\n\ntry {\n\tconst response = await fetch(url, options);\n\tconst resp = await response.json();\n\treturn JSON.stringify(resp);\n} catch (error) {\n\tconsole.error(error);\n\treturn '';\n}\n",
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"additionalParams": true,
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"id": "openAPIToolkit_0-input-customCode-code",
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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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"returnDirect": "",
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"headers": "",
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"removeNulls": "",
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"customCode": "const fetch = require('node-fetch');\nconst url = $url;\nconst options = $options;\n\ntry {\n\tconst response = await fetch(url, options);\n\tconst resp = await response.json();\n\treturn JSON.stringify(resp);\n} catch (error) {\n\tconsole.error(error);\n\treturn '';\n}\n"
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},
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"outputAnchors": [
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{
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"id": "openAPIToolkit_0-output-openAPIToolkit-OpenAPIToolkit|Tool",
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"name": "openAPIToolkit",
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"label": "OpenAPIToolkit",
|
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"description": "Load OpenAPI specification, and converts each API endpoint to a tool",
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"type": "OpenAPIToolkit | Tool"
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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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"selected": false,
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}
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],
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"edges": [
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{
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"source": "bufferMemory_0",
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"sourceHandle": "bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory",
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"target": "toolAgent_0",
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"targetHandle": "toolAgent_0-input-memory-BaseChatMemory",
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"type": "buttonedge",
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"id": "bufferMemory_0-bufferMemory_0-output-bufferMemory-BufferMemory|BaseChatMemory|BaseMemory-toolAgent_0-toolAgent_0-input-memory-BaseChatMemory"
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},
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{
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"source": "openAPIToolkit_0",
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"sourceHandle": "openAPIToolkit_0-output-openAPIToolkit-OpenAPIToolkit|Tool",
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"target": "toolAgent_0",
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|
|
"id": "openAPIToolkit_0-openAPIToolkit_0-output-openAPIToolkit-OpenAPIToolkit|Tool-toolAgent_0-toolAgent_0-input-tools-Tool"
|
|
},
|
|
{
|
|
"source": "chatAnthropic_0",
|
|
"sourceHandle": "chatAnthropic_0-output-chatAnthropic-ChatAnthropic|ChatAnthropicMessages|BaseChatModel|BaseLanguageModel|Runnable",
|
|
"target": "toolAgent_0",
|
|
"targetHandle": "toolAgent_0-input-model-BaseChatModel",
|
|
"type": "buttonedge",
|
|
"id": "chatAnthropic_0-chatAnthropic_0-output-chatAnthropic-ChatAnthropic|ChatAnthropicMessages|BaseChatModel|BaseLanguageModel|Runnable-toolAgent_0-toolAgent_0-input-model-BaseChatModel"
|
|
}
|
|
]
|
|
}
|