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import dotenv from 'dotenv';
import { XMLBuilder, XMLParser } from 'fast-xml-parser';
import { escape } from 'lodash'; // Imported escape from lodash
import OpenAI from 'openai';
import { DocumentOptions } from '../../../../documents/Documents';
import { AnswerParser } from '../response_parsers/AnswerParser';
import { StreamedAnswerParser } from '../response_parsers/StreamedAnswerParser';
import { BaseTool } from '../tools/BaseTool';
import { CalculateTool } from '../tools/CalculateTool';
//import { CreateAnyDocumentTool } from '../tools/CreateAnyDocTool';
import { CreateDocTool } from '../tools/CreateDocumentTool';
import { DataAnalysisTool } from '../tools/DataAnalysisTool';
import { ImageCreationTool } from '../tools/ImageCreationTool';
import { NoTool } from '../tools/NoTool';
import { SearchTool } from '../tools/SearchTool';
import { Parameter, ParametersType, TypeMap } from '../types/tool_types';
import { AgentMessage, ASSISTANT_ROLE, AssistantMessage, Observation, PROCESSING_TYPE, ProcessingInfo, TEXT_TYPE } from '../types/types';
import { Vectorstore } from '../vectorstore/Vectorstore';
import { getReactPrompt } from './prompts';
//import { DictionaryTool } from '../tools/DictionaryTool';
import { ChatCompletionMessageParam } from 'openai/resources';
import { Doc } from '../../../../../fields/Doc';
import { parsedDoc } from '../chatboxcomponents/ChatBox';
import { WebsiteInfoScraperTool } from '../tools/WebsiteInfoScraperTool';
import { Upload } from '../../../../../server/SharedMediaTypes';
import { RAGTool } from '../tools/RAGTool';
//import { CreateTextDocTool } from '../tools/CreateTextDocumentTool';
dotenv.config();
/**
* The Agent class handles the interaction between the assistant and the tools available,
* processes user queries, and manages the communication flow between the tools and OpenAI.
*/
export class Agent {
// Private properties
private client: OpenAI;
private messages: AgentMessage[] = [];
private interMessages: AgentMessage[] = [];
private vectorstore: Vectorstore;
private _history: () => string;
private _summaries: () => string;
private _csvData: () => { filename: string; id: string; text: string }[];
private actionNumber: number = 0;
private thoughtNumber: number = 0;
private processingNumber: number = 0;
private processingInfo: ProcessingInfo[] = [];
private streamedAnswerParser: StreamedAnswerParser = new StreamedAnswerParser();
private tools: Record<string, BaseTool<ReadonlyArray<Parameter>>>;
/**
* The constructor initializes the agent with the vector store and toolset, and sets up the OpenAI client.
* @param _vectorstore Vector store instance for document storage and retrieval.
* @param summaries A function to retrieve document summaries.
* @param history A function to retrieve chat history.
* @param csvData A function to retrieve CSV data linked to the assistant.
* @param addLinkedUrlDoc A function to add a linked document from a URL.
* @param createCSVInDash A function to create a CSV document in the dashboard.
*/
constructor(
_vectorstore: Vectorstore,
summaries: () => string,
history: () => string,
csvData: () => { filename: string; id: string; text: string }[],
addLinkedUrlDoc: (url: string, id: string) => void,
createImage: (result: Upload.FileInformation & Upload.InspectionResults, options: DocumentOptions) => void,
addLinkedDoc: (doc: parsedDoc) => Doc | undefined,
// eslint-disable-next-line @typescript-eslint/no-unused-vars
createCSVInDash: (url: string, title: string, id: string, data: string) => void
) {
// Initialize OpenAI client with API key from environment
this.client = new OpenAI({ apiKey: process.env.OPENAI_KEY, dangerouslyAllowBrowser: true });
this.vectorstore = _vectorstore;
this._history = history;
this._summaries = summaries;
this._csvData = csvData;
// Define available tools for the assistant
this.tools = {
calculate: new CalculateTool(),
rag: new RAGTool(this.vectorstore),
dataAnalysis: new DataAnalysisTool(csvData),
websiteInfoScraper: new WebsiteInfoScraperTool(addLinkedUrlDoc),
searchTool: new SearchTool(addLinkedUrlDoc),
// createCSV: new CreateCSVTool(createCSVInDash),
noTool: new NoTool(),
imageCreationTool: new ImageCreationTool(createImage),
// createTextDoc: new CreateTextDocTool(addLinkedDoc),
createDoc: new CreateDocTool(addLinkedDoc),
// createAnyDocument: new CreateAnyDocumentTool(addLinkedDoc),
// dictionary: new DictionaryTool(),
};
}
/**
* This method handles the conversation flow with the assistant, processes user queries,
* and manages the assistant's decision-making process, including tool actions.
* @param question The user's question.
* @param onProcessingUpdate Callback function for processing updates.
* @param onAnswerUpdate Callback function for answer updates.
* @param maxTurns The maximum number of turns to allow in the conversation.
* @returns The final response from the assistant.
*/
async askAgent(question: string, onProcessingUpdate: (processingUpdate: ProcessingInfo[]) => void, onAnswerUpdate: (answerUpdate: string) => void, maxTurns: number = 30): Promise<AssistantMessage> {
console.log(`Starting query: ${question}`);
const MAX_QUERY_LENGTH = 1000; // adjust the limit as needed
// Check if the question exceeds the maximum length
if (question.length > MAX_QUERY_LENGTH) {
return { role: ASSISTANT_ROLE.ASSISTANT, content: [{ text: 'User query too long. Please shorten your question and try again.', index: 0, type: TEXT_TYPE.NORMAL, citation_ids: null }], processing_info: [] };
}
const sanitizedQuestion = escape(question); // Sanitized user input
// Push sanitized user's question to message history
this.messages.push({ role: 'user', content: sanitizedQuestion });
// Retrieve chat history and generate system prompt
const chatHistory = this._history();
const systemPrompt = getReactPrompt(Object.values(this.tools), this._summaries, chatHistory);
// Initialize intermediate messages
this.interMessages = [{ role: 'system', content: systemPrompt }];
this.interMessages.push({
role: 'user',
content: this.constructUserPrompt(1, 'user', `<query>${sanitizedQuestion}</query>`),
});
// Setup XML parser and builder
const parser = new XMLParser({
ignoreAttributes: false,
attributeNamePrefix: '@_',
textNodeName: '_text',
isArray: name => ['query', 'url'].indexOf(name) !== -1,
processEntities: false, // Disable processing of entities
stopNodes: ['*.entity'], // Do not process any entities
});
const builder = new XMLBuilder({ ignoreAttributes: false, attributeNamePrefix: '@_' });
let currentAction: string | undefined;
this.processingInfo = [];
let i = 2;
while (i < maxTurns) {
console.log(this.interMessages);
console.log(`Turn ${i}/${maxTurns}`);
// eslint-disable-next-line no-await-in-loop
const result = await this.execute(onProcessingUpdate, onAnswerUpdate);
this.interMessages.push({ role: 'assistant', content: result });
i += 2;
let parsedResult;
try {
// Parse XML result from the assistant
parsedResult = parser.parse(result);
// Validate the structure of the parsedResult
this.validateAssistantResponse(parsedResult);
} catch (error) {
throw new Error(`Error parsing or validating response: ${error}`);
}
// Extract the stage from the parsed result
const stage = parsedResult.stage;
if (!stage) {
throw new Error(`Error: No stage found in response`);
}
// Handle different stage elements (thoughts, actions, inputs, answers)
for (const key in stage) {
if (key === 'thought') {
// Handle assistant's thoughts
console.log(`Thought: ${stage[key]}`);
this.processingNumber++;
} else if (key === 'action') {
// Handle action stage
currentAction = stage[key] as string;
console.log(`Action: ${currentAction}`);
if (this.tools[currentAction]) {
// Prepare the next action based on the current tool
const nextPrompt = [
{
type: 'text',
text: `<stage number="${i + 1}" role="user">` + builder.build({ action_rules: this.tools[currentAction].getActionRule() }) + `</stage>`,
} as Observation,
];
this.interMessages.push({ role: 'user', content: nextPrompt });
break;
} else {
// Handle error in case of an invalid action
console.log('Error: No valid action');
this.interMessages.push({
role: 'user',
content: `<stage number="${i + 1}" role="system-error-reporter">No valid action, try again.</stage>`,
});
break;
}
} else if (key === 'action_input') {
// Handle action input stage
const actionInput = stage[key];
console.log(`Action input full:`, actionInput);
console.log(`Action input:`, actionInput.inputs);
if (currentAction) {
try {
// Process the action with its input
// eslint-disable-next-line no-await-in-loop
const observation = (await this.processAction(currentAction, actionInput.inputs)) as Observation[];
const nextPrompt = [{ type: 'text', text: `<stage number="${i + 1}" role="user"> <observation>` }, ...observation, { type: 'text', text: '</observation></stage>' }] as Observation[];
console.log(observation);
this.interMessages.push({ role: 'user', content: nextPrompt });
this.processingNumber++;
break;
} catch (error) {
throw new Error(`Error processing action: ${error}`);
}
} else {
throw new Error('Error: Action input without a valid action');
}
} else if (key === 'answer') {
// If an answer is found, end the query
console.log('Answer found. Ending query.');
this.streamedAnswerParser.reset();
const parsedAnswer = AnswerParser.parse(result, this.processingInfo);
return parsedAnswer;
}
}
}
throw new Error('Reached maximum turns. Ending query.');
}
private constructUserPrompt(stageNumber: number, role: string, content: string): string {
return `<stage number="${stageNumber}" role="${role}">${content}</stage>`;
}
/**
* Executes a step in the conversation, processing the assistant's response and parsing it in real-time.
* @param onProcessingUpdate Callback for processing updates.
* @param onAnswerUpdate Callback for answer updates.
* @returns The full response from the assistant.
*/
private async execute(onProcessingUpdate: (processingUpdate: ProcessingInfo[]) => void, onAnswerUpdate: (answerUpdate: string) => void): Promise<string> {
// Stream OpenAI response for real-time updates
const stream = await this.client.chat.completions.create({
model: 'gpt-4o',
messages: this.interMessages as ChatCompletionMessageParam[],
temperature: 0,
stream: true,
stop: ['</stage>'],
});
let fullResponse: string = '';
let currentTag: string = '';
let currentContent: string = '';
let isInsideTag: boolean = false;
// Process each chunk of the streamed response
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content || '';
fullResponse += content;
// Parse the streamed content character by character
for (const char of content) {
if (currentTag === 'answer') {
// Handle answer parsing for real-time updates
currentContent += char;
const streamedAnswer = this.streamedAnswerParser.parse(char);
onAnswerUpdate(streamedAnswer);
continue;
} else if (char === '<') {
// Start of a new tag
isInsideTag = true;
currentTag = '';
currentContent = '';
} else if (char === '>') {
// End of the tag
isInsideTag = false;
if (currentTag.startsWith('/')) {
currentTag = '';
}
} else if (isInsideTag) {
// Append characters to the tag name
currentTag += char;
} else if (currentTag === 'thought' || currentTag === 'action_input_description') {
// Handle processing information for thought or action input description
currentContent += char;
const current_info = this.processingInfo.find(info => info.index === this.processingNumber);
if (current_info) {
current_info.content = currentContent.trim();
onProcessingUpdate(this.processingInfo);
} else {
this.processingInfo.push({
index: this.processingNumber,
type: currentTag === 'thought' ? PROCESSING_TYPE.THOUGHT : PROCESSING_TYPE.ACTION,
content: currentContent.trim(),
});
onProcessingUpdate(this.processingInfo);
}
}
}
}
return fullResponse;
}
/**
* Validates the assistant's response to ensure it conforms to the expected XML structure.
* @param response The parsed XML response from the assistant.
* @throws An error if the response does not meet the expected structure.
*/
private validateAssistantResponse(response: { stage: { [key: string]: object | string } }) {
if (!response.stage) {
throw new Error('Response does not contain a <stage> element');
}
// Validate that the stage has the required attributes
const stage = response.stage;
if (!stage['@_number'] || !stage['@_role']) {
throw new Error('Stage element must have "number" and "role" attributes');
}
// Extract the role of the stage to determine expected content
const role = stage['@_role'];
// Depending on the role, validate the presence of required elements
if (role === 'assistant') {
// Assistant's response should contain either 'thought', 'action', 'action_input', or 'answer'
if (!('thought' in stage || 'action' in stage || 'action_input' in stage || 'answer' in stage)) {
throw new Error('Assistant stage must contain a thought, action, action_input, or answer element');
}
// If 'thought' is present, validate it
if ('thought' in stage) {
if (typeof stage.thought !== 'string' || stage.thought.trim() === '') {
throw new Error('Thought must be a non-empty string');
}
}
// If 'action' is present, validate it
if ('action' in stage) {
if (typeof stage.action !== 'string' || stage.action.trim() === '') {
throw new Error('Action must be a non-empty string');
}
// Optional: Check if the action is among allowed actions
const allowedActions = Object.keys(this.tools);
if (!allowedActions.includes(stage.action)) {
throw new Error(`Action "${stage.action}" is not a valid tool`);
}
}
// If 'action_input' is present, validate its structure
if ('action_input' in stage) {
const actionInput = stage.action_input as object;
if (!('action_input_description' in actionInput) || typeof actionInput.action_input_description !== 'string') {
throw new Error('action_input must contain an action_input_description string');
}
if (!('inputs' in actionInput)) {
throw new Error('action_input must contain an inputs object');
}
// Further validation of inputs can be done here based on the expected parameters of the action
}
// If 'answer' is present, validate its structure
if ('answer' in stage) {
const answer = stage.answer as object;
// Ensure answer contains at least one of the required elements
if (!('grounded_text' in answer || 'normal_text' in answer)) {
throw new Error('Answer must contain grounded_text or normal_text');
}
// Validate follow_up_questions
if (!('follow_up_questions' in answer)) {
throw new Error('Answer must contain follow_up_questions');
}
// Validate loop_summary
if (!('loop_summary' in answer)) {
throw new Error('Answer must contain a loop_summary');
}
// Additional validation for citations, grounded_text, etc., can be added here
}
} else if (role === 'user') {
// User's stage should contain 'query' or 'observation'
if (!('query' in stage || 'observation' in stage)) {
throw new Error('User stage must contain a query or observation element');
}
// Validate 'query' if present
if ('query' in stage && typeof stage.query !== 'string') {
throw new Error('Query must be a string');
}
// Validate 'observation' if present
if ('observation' in stage) {
// Ensure observation has the correct structure
// This can be expanded based on how observations are structured
}
} else {
throw new Error(`Unknown role "${role}" in stage`);
}
// Add any additional validation rules as necessary
}
/**
* Helper function to check if a string can be parsed as an array of the expected type.
* @param input The input string to check.
* @param expectedType The expected type of the array elements ('string', 'number', or 'boolean').
* @returns The parsed array if valid, otherwise throws an error.
*/
private parseArray<T>(input: string, expectedType: 'string' | 'number' | 'boolean'): T[] {
try {
// Parse the input string into a JSON object
const parsed = JSON.parse(input);
// Check if the parsed object is an array and if all elements are of the expected type
if (Array.isArray(parsed) && parsed.every(item => typeof item === expectedType)) {
return parsed;
} else {
throw new Error(`Invalid ${expectedType} array format.`);
}
} catch (error) {
throw new Error(`Failed to parse ${expectedType} array: ` + error);
}
}
/**
* Processes a specific action by invoking the appropriate tool with the provided inputs.
* This method ensures that the action exists and validates the types of `actionInput`
* based on the tool's parameter rules. It throws errors for missing required parameters
* or mismatched types before safely executing the tool with the validated input.
*
* NOTE: In the future, it should typecheck for specific tool parameter types using the `TypeMap` or otherwise.
*
* Type validation includes checks for:
* - `string`, `number`, `boolean`
* - `string[]`, `number[]` (arrays of strings or numbers)
*
* @param action The action to perform. It corresponds to a registered tool.
* @param actionInput The inputs for the action, passed as an object where each key is a parameter name.
* @returns A promise that resolves to an array of `Observation` objects representing the result of the action.
* @throws An error if the action is unknown, if required parameters are missing, or if input types don't match the expected parameter types.
*/
private async processAction(action: string, actionInput: ParametersType<ReadonlyArray<Parameter>>): Promise<Observation[]> {
// Check if the action exists in the tools list
if (!(action in this.tools)) {
throw new Error(`Unknown action: ${action}`);
}
console.log(actionInput);
for (const param of this.tools[action].parameterRules) {
// Check if the parameter is required and missing in the input
if (param.required && !(param.name in actionInput) && !this.tools[action].inputValidator(actionInput)) {
throw new Error(`Missing required parameter: ${param.name}`);
}
// Check if the parameter type matches the expected type
const expectedType = param.type.replace('[]', '') as 'string' | 'number' | 'boolean';
const isArray = param.type.endsWith('[]');
const input = actionInput[param.name];
if (isArray) {
// Check if the input is a valid array of the expected type
const parsedArray = this.parseArray(input as string, expectedType);
actionInput[param.name] = parsedArray as TypeMap[typeof param.type];
} else if (input !== undefined && typeof input !== expectedType) {
throw new Error(`Invalid type for parameter ${param.name}: expected ${expectedType}`);
}
}
const tool = this.tools[action];
return await tool.execute(actionInput);
}
}
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