mirror of
https://github.com/danny-avila/LibreChat.git
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* wip: OpenAI Image Generation Tool with customizable options * WIP: First pass OpenAI Image Generation Tool and integrate into existing tools * 🔀 fix: Comment out unused validation for image generation tool parameters * 🔀 refactor: Update primeResources function parameters for better destructuring * feat: Add image_edit resource to EToolResources and update AgentToolResources interface * feat: Enhance file retrieval with tool resource filtering for image editing * refactor: add OpenAI Image Tools for generation and editing, refactor related components, pass current request image attachments as tool resources for editing * refactor: Remove commented-out code and clean up API key retrieval in createOpenAIImageTools function * fix: show message attachments in shared links * fix: Correct parent message retrieval logic for regenerated messages in useChatFunctions * fix: Update primeResources to utilize requestFileSet for image file processing * refactor: Improve description for image generation tool and clarify usage conditions, only provide edit tool if there are images available to edit * chore: Update OpenAI Image Tools icon to use local asset * refactor: Update image generation tool description and logic to prioritize editing tool when files are uploaded * refactor: Enhance image tool descriptions to clarify usage conditions and note potential unavailability of uploaded images * refactor: Update useAttachmentHandler to accept queryClient to update query cache with newly created file * refactor: Add customizable descriptions and prompts for OpenAI image generation and editing tools * chore: Update comments to use JSDoc style for better clarity and consistency * refactor: Rename config variable to clientConfig for clarity and update signal handling in image generation * refactor: Update axios request configuration to include derived signal and baseURL for improved request handling * refactor: Update baseURL environment variable for OpenAI image generation tool configuration * refactor: Enhance axios request configuration with conditional headers and improved clientConfig setup * chore: Update comments for clarity and remove unnecessary lines in OpenAI image tools * refactor: Update description for image generation without files to clarify user instructions * refactor: Simplify target parent message logic for regeneration and resubmission cases * chore: Remove backticks from error messages in image generation and editing functions * refactor: Rename toolResources to toolResourceSet for clarity in file retrieval functions * chore: Remove redundant comments and clean up TODOs in OpenAI image tools * refactor: Rename fileStrategy to appFileStrategy for clarity and improve error handling in image processing * chore: Update react-resizable-panels to version 2.1.8 in package.json and package-lock.json * chore: Ensure required validation for logs and Code of Conduct agreement in bug report template * fix: Update ArtifactPreview to use startupConfig and currentCode from memoized props to prevent unnecessary re-renders * fix: improve robustness of `save & submit` when used from a user-message with existing attachments * fix: add null check for artifact index in CodeEditor to prevent errors, trigger re-render on artifact ID change * fix: standardize default values for artifact properties in Artifact component, avoiding prematurely setting an "empty/default" artifact * fix: reset current artifact ID before setting a new one in ArtifactButton to ensure correct state management * chore: rename `setArtifactId` variable to `setCurrentArtifactId` for consistency * chore: update type annotations in File and S3 CRUD functions for consistency * refactor: improve image handling in OpenAI tools by using image_id references and enhance tool context for image editing * fix: update image_ids schema in image_edit_oai to enforce presence and provide clear guidelines for usage * fix: enhance file fetching logic to ensure user-specific and dimension-validated results * chore: add details on image generation and editing capabilities with various models
343 lines
11 KiB
JavaScript
343 lines
11 KiB
JavaScript
const { nanoid } = require('nanoid');
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const { Tools, StepTypes, FileContext } = require('librechat-data-provider');
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const {
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EnvVar,
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Providers,
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GraphEvents,
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getMessageId,
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ToolEndHandler,
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handleToolCalls,
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ChatModelStreamHandler,
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} = require('@librechat/agents');
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const { processCodeOutput } = require('~/server/services/Files/Code/process');
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const { loadAuthValues } = require('~/server/services/Tools/credentials');
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const { saveBase64Image } = require('~/server/services/Files/process');
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const { logger, sendEvent } = require('~/config');
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/** @typedef {import('@librechat/agents').Graph} Graph */
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/** @typedef {import('@librechat/agents').EventHandler} EventHandler */
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/** @typedef {import('@librechat/agents').ModelEndData} ModelEndData */
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/** @typedef {import('@librechat/agents').ToolEndData} ToolEndData */
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/** @typedef {import('@librechat/agents').ToolEndCallback} ToolEndCallback */
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/** @typedef {import('@librechat/agents').ChatModelStreamHandler} ChatModelStreamHandler */
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/** @typedef {import('@librechat/agents').ContentAggregatorResult['aggregateContent']} ContentAggregator */
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/** @typedef {import('@librechat/agents').GraphEvents} GraphEvents */
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class ModelEndHandler {
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/**
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* @param {Array<UsageMetadata>} collectedUsage
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*/
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constructor(collectedUsage) {
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if (!Array.isArray(collectedUsage)) {
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throw new Error('collectedUsage must be an array');
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}
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this.collectedUsage = collectedUsage;
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}
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/**
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* @param {string} event
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* @param {ModelEndData | undefined} data
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* @param {Record<string, unknown> | undefined} metadata
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* @param {Graph} graph
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* @returns
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*/
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handle(event, data, metadata, graph) {
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if (!graph || !metadata) {
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console.warn(`Graph or metadata not found in ${event} event`);
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return;
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}
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try {
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if (metadata.provider === Providers.GOOGLE || graph.clientOptions?.disableStreaming) {
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handleToolCalls(data?.output?.tool_calls, metadata, graph);
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}
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const usage = data?.output?.usage_metadata;
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if (!usage) {
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return;
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}
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if (metadata?.model) {
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usage.model = metadata.model;
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}
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this.collectedUsage.push(usage);
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if (!graph.clientOptions?.disableStreaming) {
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return;
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}
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if (!data.output.content) {
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return;
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}
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const stepKey = graph.getStepKey(metadata);
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const message_id = getMessageId(stepKey, graph) ?? '';
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if (message_id) {
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graph.dispatchRunStep(stepKey, {
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type: StepTypes.MESSAGE_CREATION,
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message_creation: {
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message_id,
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},
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});
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}
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const stepId = graph.getStepIdByKey(stepKey);
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const content = data.output.content;
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if (typeof content === 'string') {
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graph.dispatchMessageDelta(stepId, {
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content: [
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{
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type: 'text',
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text: content,
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},
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],
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});
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} else if (content.every((c) => c.type?.startsWith('text'))) {
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graph.dispatchMessageDelta(stepId, {
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content,
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});
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}
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} catch (error) {
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logger.error('Error handling model end event:', error);
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}
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}
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}
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/**
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* Get default handlers for stream events.
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* @param {Object} options - The options object.
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* @param {ServerResponse} options.res - The options object.
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* @param {ContentAggregator} options.aggregateContent - The options object.
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* @param {ToolEndCallback} options.toolEndCallback - Callback to use when tool ends.
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* @param {Array<UsageMetadata>} options.collectedUsage - The list of collected usage metadata.
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* @returns {Record<string, t.EventHandler>} The default handlers.
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* @throws {Error} If the request is not found.
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*/
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function getDefaultHandlers({ res, aggregateContent, toolEndCallback, collectedUsage }) {
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if (!res || !aggregateContent) {
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throw new Error(
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`[getDefaultHandlers] Missing required options: res: ${!res}, aggregateContent: ${!aggregateContent}`,
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);
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}
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const handlers = {
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[GraphEvents.CHAT_MODEL_END]: new ModelEndHandler(collectedUsage),
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[GraphEvents.TOOL_END]: new ToolEndHandler(toolEndCallback),
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[GraphEvents.CHAT_MODEL_STREAM]: new ChatModelStreamHandler(),
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[GraphEvents.ON_RUN_STEP]: {
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/**
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* Handle ON_RUN_STEP event.
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* @param {string} event - The event name.
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* @param {StreamEventData} data - The event data.
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* @param {GraphRunnableConfig['configurable']} [metadata] The runnable metadata.
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*/
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handle: (event, data, metadata) => {
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if (data?.stepDetails.type === StepTypes.TOOL_CALLS) {
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sendEvent(res, { event, data });
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} else if (metadata?.last_agent_index === metadata?.agent_index) {
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sendEvent(res, { event, data });
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} else if (!metadata?.hide_sequential_outputs) {
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sendEvent(res, { event, data });
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} else {
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const agentName = metadata?.name ?? 'Agent';
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const isToolCall = data?.stepDetails.type === StepTypes.TOOL_CALLS;
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const action = isToolCall ? 'performing a task...' : 'thinking...';
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sendEvent(res, {
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event: 'on_agent_update',
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data: {
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runId: metadata?.run_id,
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message: `${agentName} is ${action}`,
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},
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});
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}
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aggregateContent({ event, data });
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},
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},
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[GraphEvents.ON_RUN_STEP_DELTA]: {
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/**
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* Handle ON_RUN_STEP_DELTA event.
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* @param {string} event - The event name.
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* @param {StreamEventData} data - The event data.
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* @param {GraphRunnableConfig['configurable']} [metadata] The runnable metadata.
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*/
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handle: (event, data, metadata) => {
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if (data?.delta.type === StepTypes.TOOL_CALLS) {
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sendEvent(res, { event, data });
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} else if (metadata?.last_agent_index === metadata?.agent_index) {
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sendEvent(res, { event, data });
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} else if (!metadata?.hide_sequential_outputs) {
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sendEvent(res, { event, data });
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}
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aggregateContent({ event, data });
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},
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},
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[GraphEvents.ON_RUN_STEP_COMPLETED]: {
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/**
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* Handle ON_RUN_STEP_COMPLETED event.
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* @param {string} event - The event name.
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* @param {StreamEventData & { result: ToolEndData }} data - The event data.
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* @param {GraphRunnableConfig['configurable']} [metadata] The runnable metadata.
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*/
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handle: (event, data, metadata) => {
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if (data?.result != null) {
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sendEvent(res, { event, data });
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} else if (metadata?.last_agent_index === metadata?.agent_index) {
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sendEvent(res, { event, data });
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} else if (!metadata?.hide_sequential_outputs) {
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sendEvent(res, { event, data });
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}
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aggregateContent({ event, data });
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},
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},
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[GraphEvents.ON_MESSAGE_DELTA]: {
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/**
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* Handle ON_MESSAGE_DELTA event.
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* @param {string} event - The event name.
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* @param {StreamEventData} data - The event data.
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* @param {GraphRunnableConfig['configurable']} [metadata] The runnable metadata.
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*/
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handle: (event, data, metadata) => {
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if (metadata?.last_agent_index === metadata?.agent_index) {
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sendEvent(res, { event, data });
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} else if (!metadata?.hide_sequential_outputs) {
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sendEvent(res, { event, data });
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}
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aggregateContent({ event, data });
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},
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},
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[GraphEvents.ON_REASONING_DELTA]: {
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/**
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* Handle ON_REASONING_DELTA event.
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* @param {string} event - The event name.
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* @param {StreamEventData} data - The event data.
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* @param {GraphRunnableConfig['configurable']} [metadata] The runnable metadata.
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*/
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handle: (event, data, metadata) => {
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if (metadata?.last_agent_index === metadata?.agent_index) {
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sendEvent(res, { event, data });
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} else if (!metadata?.hide_sequential_outputs) {
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sendEvent(res, { event, data });
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}
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aggregateContent({ event, data });
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},
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},
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};
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return handlers;
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}
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/**
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*
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* @param {Object} params
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* @param {ServerRequest} params.req
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* @param {ServerResponse} params.res
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* @param {Promise<MongoFile | { filename: string; filepath: string; expires: number;} | null>[]} params.artifactPromises
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* @returns {ToolEndCallback} The tool end callback.
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*/
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function createToolEndCallback({ req, res, artifactPromises }) {
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/**
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* @type {ToolEndCallback}
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*/
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return async (data, metadata) => {
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const output = data?.output;
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if (!output) {
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return;
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}
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if (!output.artifact) {
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return;
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}
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if (output.artifact.content) {
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/** @type {FormattedContent[]} */
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const content = output.artifact.content;
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for (let i = 0; i < content.length; i++) {
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const part = content[i];
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if (!part) {
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continue;
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}
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if (part.type !== 'image_url') {
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continue;
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}
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const { url } = part.image_url;
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artifactPromises.push(
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(async () => {
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const filename = `${output.name}_${output.tool_call_id}_img_${nanoid()}`;
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const file_id = output.artifact.file_ids?.[i];
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const file = await saveBase64Image(url, {
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req,
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file_id,
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filename,
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endpoint: metadata.provider,
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context: FileContext.image_generation,
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});
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const fileMetadata = Object.assign(file, {
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messageId: metadata.run_id,
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toolCallId: output.tool_call_id,
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conversationId: metadata.thread_id,
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});
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if (!res.headersSent) {
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return fileMetadata;
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}
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if (!fileMetadata) {
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return null;
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}
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res.write(`event: attachment\ndata: ${JSON.stringify(fileMetadata)}\n\n`);
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return fileMetadata;
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})().catch((error) => {
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logger.error('Error processing artifact content:', error);
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return null;
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}),
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);
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}
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return;
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}
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{
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if (output.name !== Tools.execute_code) {
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return;
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}
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}
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if (!output.artifact.files) {
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return;
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}
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for (const file of output.artifact.files) {
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const { id, name } = file;
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artifactPromises.push(
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(async () => {
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const result = await loadAuthValues({
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userId: req.user.id,
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authFields: [EnvVar.CODE_API_KEY],
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});
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const fileMetadata = await processCodeOutput({
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req,
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id,
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name,
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apiKey: result[EnvVar.CODE_API_KEY],
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messageId: metadata.run_id,
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toolCallId: output.tool_call_id,
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conversationId: metadata.thread_id,
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session_id: output.artifact.session_id,
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});
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if (!res.headersSent) {
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return fileMetadata;
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}
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if (!fileMetadata) {
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return null;
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}
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res.write(`event: attachment\ndata: ${JSON.stringify(fileMetadata)}\n\n`);
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return fileMetadata;
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})().catch((error) => {
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logger.error('Error processing code output:', error);
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return null;
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}),
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);
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}
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};
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}
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module.exports = {
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getDefaultHandlers,
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createToolEndCallback,
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};
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