dtamind-components
Version:
Apps integration for Dtamind. Contain Nodes and Credentials.
500 lines (485 loc) • 22.4 kB
JavaScript
"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
const lodash_1 = require("lodash");
const zod_1 = require("zod");
const prompts_1 = require("@langchain/core/prompts");
const runnables_1 = require("@langchain/core/runnables");
const utils_1 = require("../../../src/utils");
const commonUtils_1 = require("../commonUtils");
const examplePrompt = `You are an expert customer support routing system.
Your job is to detect whether a customer support representative is routing a user to the technical support team, or just responding conversationally.`;
const exampleHumanPrompt = `The previous conversation is an interaction between a customer support representative and a user.
Extract whether the representative is routing the user to the technical support team, or just responding conversationally.
If representative want to route the user to the technical support team, respond only with the word "TECHNICAL".
Otherwise, respond only with the word "CONVERSATION".
Remember, only respond with one of the above words.`;
const howToUseCode = `
1. Must return a string value at the end of function. For example:
\`\`\`js
if ("X" === "X") {
return "Agent"; // connect to next agent node
} else {
return "End"; // connect to end node
}
\`\`\`
2. In most cases, you would probably get the last message to do some comparison. You can get all current messages from the state: \`$flow.state.messages\`:
\`\`\`json
[
{
"content": "Hello! How can I assist you today?",
"name": "",
"additional_kwargs": {},
"response_metadata": {},
"tool_calls": [],
"invalid_tool_calls": [],
"usage_metadata": {}
}
]
\`\`\`
For example, to get the last message content:
\`\`\`js
const messages = $flow.state.messages;
const lastMessage = messages[messages.length - 1];
// Proceed to do something with the last message content
\`\`\`
3. If you want to use the Condition Agent's output for conditional checks, it is available as \`$flow.output\` with the following structure:
\`\`\`json
{
"content": 'Hello! How can I assist you today?',
"name": "",
"additional_kwargs": {},
"response_metadata": {},
"tool_calls": [],
"invalid_tool_calls": [],
"usage_metadata": {}
}
\`\`\`
For example, we can check if the agent's output contains specific keyword:
\`\`\`js
const result = $flow.output.content;
if (result.includes("some-keyword")) {
return "Agent"; // connect to next agent node
} else {
return "End"; // connect to end node
}
\`\`\`
If Structured Output is enabled, \`$flow.output\` will be in the JSON format as defined in the Structured Output configuration:
\`\`\`json
{
"foo": 'var'
}
\`\`\`
4. You can get default flow config, including the current "state":
- \`$flow.sessionId\`
- \`$flow.chatId\`
- \`$flow.chatflowId\`
- \`$flow.input\`
- \`$flow.state\`
5. You can get custom variables: \`$vars.<variable-name>\`
`;
const defaultFunc = `const result = $flow.output.content;
if (result.includes("some-keyword")) {
return "Agent";
}
return "End";
`;
const TAB_IDENTIFIER = 'selectedConditionFunctionTab';
class ConditionAgent_SeqAgents {
constructor() {
this.label = 'Condition Agent';
this.name = 'seqConditionAgent';
this.version = 3.1;
this.type = 'ConditionAgent';
this.icon = 'condition.svg';
this.category = 'Sequential Agents';
this.description = 'Uses an agent to determine which route to take next';
this.baseClasses = [this.type];
this.documentation = 'https://docs.dtamindai.com/using-dtamind/agentflows/sequential-agents#id-8.-conditional-agent-node';
this.inputs = [
{
label: 'Name',
name: 'conditionAgentName',
type: 'string',
placeholder: 'Condition Agent'
},
{
label: 'Sequential Node',
name: 'sequentialNode',
type: 'Start | Agent | LLMNode | ToolNode | CustomFunction | ExecuteFlow',
description: 'Can be connected to one of the following nodes: Start, Agent, LLM Node, Tool Node, Custom Function, Execute Flow',
list: true
},
{
label: 'Chat Model',
name: 'model',
type: 'BaseChatModel',
optional: true,
description: `Overwrite model to be used for this agent`
},
{
label: 'System Prompt',
name: 'systemMessagePrompt',
type: 'string',
rows: 4,
default: examplePrompt,
additionalParams: true,
optional: true
},
{
label: 'Conversation History',
name: 'conversationHistorySelection',
type: 'options',
options: [
{
label: 'User Question',
name: 'user_question',
description: 'Use the user question from the historical conversation messages as input.'
},
{
label: 'Last Conversation Message',
name: 'last_message',
description: 'Use the last conversation message from the historical conversation messages as input.'
},
{
label: 'All Conversation Messages',
name: 'all_messages',
description: 'Use all conversation messages from the historical conversation messages as input.'
},
{
label: 'Empty',
name: 'empty',
description: 'Do not use any messages from the conversation history. ' +
'Ensure to use either System Prompt, Human Prompt, or Messages History.'
}
],
default: 'all_messages',
optional: true,
description: 'Select which messages from the conversation history to include in the prompt. ' +
'The selected messages will be inserted between the System Prompt (if defined) and ' +
'Human Prompt.',
additionalParams: true
},
{
label: 'Human Prompt',
name: 'humanMessagePrompt',
type: 'string',
description: 'This prompt will be added at the end of the messages as human message',
rows: 4,
default: exampleHumanPrompt,
additionalParams: true,
optional: true
},
{
label: 'Format Prompt Values',
name: 'promptValues',
description: 'Assign values to the prompt variables. You can also use $flow.state.<variable-name> to get the state value',
type: 'json',
optional: true,
acceptVariable: true,
list: true,
additionalParams: true
},
{
label: 'JSON Structured Output',
name: 'conditionAgentStructuredOutput',
type: 'datagrid',
description: 'Instruct the LLM to give output in a JSON structured schema',
datagrid: [
{ field: 'key', headerName: 'Key', editable: true },
{
field: 'type',
headerName: 'Type',
type: 'singleSelect',
valueOptions: ['String', 'String Array', 'Number', 'Boolean', 'Enum'],
editable: true
},
{ field: 'enumValues', headerName: 'Enum Values', editable: true },
{ field: 'description', headerName: 'Description', flex: 1, editable: true }
],
optional: true,
additionalParams: true
},
{
label: 'Condition',
name: 'condition',
type: 'conditionFunction', // This is a custom type to show as button on the UI and render anchor points when saved
tabIdentifier: TAB_IDENTIFIER,
tabs: [
{
label: 'Condition (Table)',
name: 'conditionUI',
type: 'datagrid',
description: 'If a condition is met, the node connected to the respective output will be executed',
optional: true,
datagrid: [
{
field: 'variable',
headerName: 'Variable',
type: 'freeSolo',
editable: true,
loadMethod: ['getPreviousMessages', 'loadStateKeys'],
valueOptions: [
{
label: 'Agent Output (string)',
value: '$flow.output.content'
},
{
label: `Agent's JSON Key Output (string)`,
value: '$flow.output.<replace-with-key>'
},
{
label: 'Total Messages (number)',
value: '$flow.state.messages.length'
},
{
label: 'First Message Content (string)',
value: '$flow.state.messages[0].content'
},
{
label: 'Last Message Content (string)',
value: '$flow.state.messages[-1].content'
},
{
label: `Global variable (string)`,
value: '$vars.<variable-name>'
}
],
flex: 0.5,
minWidth: 200
},
{
field: 'operation',
headerName: 'Operation',
type: 'singleSelect',
valueOptions: [
'Contains',
'Not Contains',
'Start With',
'End With',
'Is',
'Is Not',
'Is Empty',
'Is Not Empty',
'Greater Than',
'Less Than',
'Equal To',
'Not Equal To',
'Greater Than or Equal To',
'Less Than or Equal To'
],
editable: true,
flex: 0.4,
minWidth: 150
},
{
field: 'value',
headerName: 'Value',
flex: 1,
editable: true
},
{
field: 'output',
headerName: 'Output Name',
editable: true,
flex: 0.3,
minWidth: 150
}
]
},
{
label: 'Condition (Code)',
name: 'conditionFunction',
type: 'code',
description: 'Function to evaluate the condition',
hint: {
label: 'How to use',
value: howToUseCode
},
hideCodeExecute: true,
codeExample: defaultFunc,
optional: true
}
]
}
];
this.outputs = [
{
label: 'Next',
name: 'next',
baseClasses: ['Condition'],
isAnchor: true
},
{
label: 'End',
name: 'end',
baseClasses: ['Condition'],
isAnchor: true
}
];
}
async init(nodeData, input, options) {
const conditionLabel = nodeData.inputs?.conditionAgentName;
const conditionName = conditionLabel.toLowerCase().replace(/\s/g, '_').trim();
const output = nodeData.outputs?.output;
const sequentialNodes = nodeData.inputs?.sequentialNode;
let agentPrompt = nodeData.inputs?.systemMessagePrompt;
agentPrompt = (0, utils_1.transformBracesWithColon)(agentPrompt);
let humanPrompt = nodeData.inputs?.humanMessagePrompt;
humanPrompt = (0, utils_1.transformBracesWithColon)(humanPrompt);
const promptValuesStr = nodeData.inputs?.promptValues;
const conditionAgentStructuredOutput = nodeData.inputs?.conditionAgentStructuredOutput;
const model = nodeData.inputs?.model;
if (!sequentialNodes || !sequentialNodes.length)
throw new Error('Condition Agent must have a predecessor!');
const startLLM = sequentialNodes[0].startLLM;
const llm = model || startLLM;
if (nodeData.inputs)
nodeData.inputs.model = llm;
let conditionAgentInputVariablesValues = {};
if (promptValuesStr) {
try {
conditionAgentInputVariablesValues = typeof promptValuesStr === 'object' ? promptValuesStr : JSON.parse(promptValuesStr);
}
catch (exception) {
throw new Error("Invalid JSON in the Condition Agent's Prompt Input Values: " + exception);
}
}
conditionAgentInputVariablesValues = (0, utils_1.handleEscapeCharacters)(conditionAgentInputVariablesValues, true);
const conditionAgentInputVariables = (0, lodash_1.uniq)([...(0, utils_1.getInputVariables)(agentPrompt), ...(0, utils_1.getInputVariables)(humanPrompt)]);
if (!conditionAgentInputVariables.every((element) => Object.keys(conditionAgentInputVariablesValues).includes(element))) {
throw new Error('Condition Agent input variables values are not provided!');
}
const abortControllerSignal = options.signal;
const conditionalEdge = async (state, config) => await runCondition(conditionName, nodeData, input, options, state, config, llm, agentPrompt, humanPrompt, conditionAgentInputVariablesValues, conditionAgentStructuredOutput, abortControllerSignal);
const returnOutput = {
id: nodeData.id,
node: conditionalEdge,
name: conditionName,
label: conditionLabel,
type: 'condition',
output,
llm,
startLLM,
multiModalMessageContent: sequentialNodes[0]?.multiModalMessageContent,
predecessorAgents: sequentialNodes
};
return returnOutput;
}
}
const runCondition = async (conditionName, nodeData, input, options, state, config, llm, agentPrompt, humanPrompt, conditionAgentInputVariablesValues, conditionAgentStructuredOutput, abortControllerSignal) => {
const appDataSource = options.appDataSource;
const databaseEntities = options.databaseEntities;
const tabIdentifier = nodeData.inputs?.[`${TAB_IDENTIFIER}_${nodeData.id}`];
const conditionUI = nodeData.inputs?.conditionUI;
const conditionFunction = nodeData.inputs?.conditionFunction;
const selectedTab = tabIdentifier ? tabIdentifier.split(`_${nodeData.id}`)[0] : 'conditionUI';
const promptArrays = [new prompts_1.MessagesPlaceholder('messages')];
if (agentPrompt)
promptArrays.unshift(['system', agentPrompt]);
if (humanPrompt)
promptArrays.push(['human', humanPrompt]);
const prompt = prompts_1.ChatPromptTemplate.fromMessages(promptArrays);
let model;
if (conditionAgentStructuredOutput && conditionAgentStructuredOutput !== '[]') {
try {
const structuredOutput = zod_1.z.object((0, commonUtils_1.convertStructuredSchemaToZod)(conditionAgentStructuredOutput));
// @ts-ignore
model = llm.withStructuredOutput(structuredOutput);
}
catch (exception) {
console.error('Invalid JSON in Condition Agent Structured Output: ' + exception);
model = llm;
}
}
else {
model = llm;
}
let chain;
if (!conditionAgentInputVariablesValues || !Object.keys(conditionAgentInputVariablesValues).length) {
chain = runnables_1.RunnableSequence.from([prompt, model]).withConfig({
metadata: { sequentialNodeName: conditionName }
});
}
else {
chain = runnables_1.RunnableSequence.from([
runnables_1.RunnablePassthrough.assign((0, commonUtils_1.transformObjectPropertyToFunction)(conditionAgentInputVariablesValues, state)),
prompt,
model
]).withConfig({
metadata: { sequentialNodeName: conditionName }
});
}
const historySelection = (nodeData.inputs?.conversationHistorySelection || 'all_messages');
// @ts-ignore
state.messages = (0, commonUtils_1.filterConversationHistory)(historySelection, input, state);
// @ts-ignore
state.messages = (0, commonUtils_1.restructureMessages)(model, state);
let result = await chain.invoke({ ...state, signal: abortControllerSignal?.signal }, config);
result.additional_kwargs = { ...result.additional_kwargs, nodeId: nodeData.id };
if (conditionAgentStructuredOutput && conditionAgentStructuredOutput !== '[]' && result.tool_calls && result.tool_calls.length) {
let jsonResult = {};
for (const toolCall of result.tool_calls) {
jsonResult = { ...jsonResult, ...toolCall.args };
}
result = { ...jsonResult, additional_kwargs: { nodeId: nodeData.id } };
}
const variables = await (0, utils_1.getVars)(appDataSource, databaseEntities, nodeData, options);
const flow = {
chatflowId: options.chatflowid,
sessionId: options.sessionId,
chatId: options.chatId,
input,
state,
output: result,
vars: (0, utils_1.prepareSandboxVars)(variables)
};
if (selectedTab === 'conditionFunction' && conditionFunction) {
const vm = await (0, commonUtils_1.getVM)(appDataSource, databaseEntities, nodeData, options, flow);
try {
const response = await vm.run(`module.exports = async function() {${conditionFunction}}()`, __dirname);
if (typeof response !== 'string')
throw new Error('Condition function must return a string');
return response;
}
catch (e) {
throw new Error(e);
}
}
else if (selectedTab === 'conditionUI' && conditionUI) {
try {
const conditionItems = typeof conditionUI === 'string' ? JSON.parse(conditionUI) : conditionUI;
for (const item of conditionItems) {
if (!item.variable)
throw new Error('Condition variable is required!');
if (item.variable.startsWith('$flow')) {
const variableValue = (0, commonUtils_1.customGet)(flow, item.variable.replace('$flow.', ''));
if ((0, commonUtils_1.checkCondition)(variableValue, item.operation, item.value)) {
return item.output;
}
}
else if (item.variable.startsWith('$vars')) {
const variableValue = (0, commonUtils_1.customGet)(flow, item.variable.replace('$', ''));
if ((0, commonUtils_1.checkCondition)(variableValue, item.operation, item.value)) {
return item.output;
}
}
else if (item.variable.startsWith('$')) {
const nodeId = item.variable.replace('$', '');
const messageOutputs = (state.messages ?? []).filter((message) => message.additional_kwargs && message.additional_kwargs?.nodeId === nodeId);
const messageOutput = messageOutputs[messageOutputs.length - 1];
if (messageOutput) {
if ((0, commonUtils_1.checkCondition)(messageOutput.content, item.operation, item.value)) {
return item.output;
}
}
}
}
return 'End';
}
catch (exception) {
throw new Error('Invalid Condition: ' + exception);
}
}
};
module.exports = { nodeClass: ConditionAgent_SeqAgents };
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