mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-09-22 08:12:00 +02:00

* 📝 chore: Add comment to clarify purpose of check_updates.sh script
* feat: mcp package
* feat: add librechat-mcp package and update dependencies
* feat: refactor MCPConnectionSingleton to handle transport initialization and connection management
* feat: change private methods to public in MCPConnectionSingleton for improved accessibility
* feat: filesystem demo
* chore: everything demo and move everything under mcp workspace
* chore: move ts-node to mcp workspace
* feat: mcp examples
* feat: working sse MCP example
* refactor: rename MCPConnectionSingleton to MCPConnection for clarity
* refactor: replace MCPConnectionSingleton with MCPConnection for consistency
* refactor: manager/connections
* refactor: update MCPConnection to use type definitions from mcp types
* refactor: update MCPManager to use winston logger and enhance server initialization
* refactor: share logger between connections and manager
* refactor: add schema definitions and update MCPManager to accept logger parameter
* feat: map available MCP tools
* feat: load manifest tools
* feat: add MCP tools delimiter constant and update plugin key generation
* feat: call MCP tools
* feat: update librechat-data-provider version to 0.7.63 and enhance StdioOptionsSchema with additional properties
* refactor: simplify typing
* chore: update types/packages
* feat: MCP Tool Content parsing
* chore: update dependencies and improve package configurations
* feat: add 'mcp' directory to package and update configurations
* refactor: return CONTENT_AND_ARTIFACT format for MCP callTool
* chore: bump @librechat/agents
* WIP: MCP artifacts
* chore: bump @librechat/agents to v1.8.7
* fix: ensure filename has extension when saving base64 image
* fix: move base64 buffer conversion before filename extension check
* chore: update backend review workflow to install MCP package
* fix: use correct `mime` method
* fix: enhance file metadata with message and tool call IDs in image saving process
* fix: refactor ToolCall component to handle MCP tool calls and improve domain extraction
* fix: update ToolItem component for default isInstalled value and improve localization in ToolSelectDialog
* fix: update ToolItem component to use consistent text color for tool description
* style: add theming to ToolSelectDialog
* fix: improve domain extraction logic in ToolCall component
* refactor: conversation item theming, fix rename UI bug, optimize props, add missing types
* feat: enhance MCP options schema with base options (iconPath to start) and make transport type optional, infer based on other option fields
* fix: improve reconnection logic with parallel init and exponential backoff and enhance transport debug logging
* refactor: improve logging format
* refactor: improve logging of available tools by displaying tool names
* refactor: improve reconnection/connection logic
* feat: add MCP package build process to Dockerfile
* feat: add fallback icon for tools without an image in ToolItem component
* feat: Assistants Support for MCP Tools
* fix(build): configure rollup to use output.dir for dynamic imports
* chore: update @librechat/agents to version 1.8.8 and add @langchain/anthropic dependency
* fix: update CONFIG_VERSION to 1.2.0
506 lines
16 KiB
JavaScript
506 lines
16 KiB
JavaScript
const fs = require('fs');
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const path = require('path');
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const { zodToJsonSchema } = require('zod-to-json-schema');
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const { tool: toolFn, Tool } = require('@langchain/core/tools');
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const { Calculator } = require('@langchain/community/tools/calculator');
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const {
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Tools,
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ErrorTypes,
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ContentTypes,
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imageGenTools,
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actionDelimiter,
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ImageVisionTool,
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openapiToFunction,
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validateAndParseOpenAPISpec,
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} = require('librechat-data-provider');
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const { processFileURL, uploadImageBuffer } = require('~/server/services/Files/process');
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const { loadActionSets, createActionTool, domainParser } = require('./ActionService');
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const { recordUsage } = require('~/server/services/Threads');
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const { loadTools } = require('~/app/clients/tools/util');
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const { redactMessage } = require('~/config/parsers');
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const { sleep } = require('~/server/utils');
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const { logger } = require('~/config');
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/**
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* Loads and formats tools from the specified tool directory.
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*
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* The directory is scanned for JavaScript files, excluding any files in the filter set.
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* For each file, it attempts to load the file as a module and instantiate a class, if it's a subclass of `StructuredTool`.
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* Each tool instance is then formatted to be compatible with the OpenAI Assistant.
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* Additionally, instances of LangChain Tools are included in the result.
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*
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* @param {object} params - The parameters for the function.
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* @param {string} params.directory - The directory path where the tools are located.
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* @param {Array<string>} [params.adminFilter=[]] - Array of admin-defined tool keys to exclude from loading.
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* @param {Array<string>} [params.adminIncluded=[]] - Array of admin-defined tool keys to include from loading.
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* @returns {Record<string, FunctionTool>} An object mapping each tool's plugin key to its instance.
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*/
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function loadAndFormatTools({ directory, adminFilter = [], adminIncluded = [] }) {
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const filter = new Set([...adminFilter]);
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const included = new Set(adminIncluded);
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const tools = [];
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/* Structured Tools Directory */
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const files = fs.readdirSync(directory);
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if (included.size > 0 && adminFilter.length > 0) {
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logger.warn(
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'Both `includedTools` and `filteredTools` are defined; `filteredTools` will be ignored.',
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);
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}
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for (const file of files) {
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const filePath = path.join(directory, file);
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if (!file.endsWith('.js') || (filter.has(file) && included.size === 0)) {
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continue;
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}
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let ToolClass = null;
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try {
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ToolClass = require(filePath);
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} catch (error) {
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logger.error(`[loadAndFormatTools] Error loading tool from ${filePath}:`, error);
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continue;
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}
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if (!ToolClass || !(ToolClass.prototype instanceof Tool)) {
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continue;
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}
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let toolInstance = null;
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try {
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toolInstance = new ToolClass({ override: true });
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} catch (error) {
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logger.error(
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`[loadAndFormatTools] Error initializing \`${file}\` tool; if it requires authentication, is the \`override\` field configured?`,
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error,
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);
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continue;
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}
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if (!toolInstance) {
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continue;
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}
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if (filter.has(toolInstance.name) && included.size === 0) {
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continue;
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}
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if (included.size > 0 && !included.has(file) && !included.has(toolInstance.name)) {
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continue;
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}
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const formattedTool = formatToOpenAIAssistantTool(toolInstance);
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tools.push(formattedTool);
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}
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/** Basic Tools; schema: { input: string } */
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const basicToolInstances = [new Calculator()];
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for (const toolInstance of basicToolInstances) {
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const formattedTool = formatToOpenAIAssistantTool(toolInstance);
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tools.push(formattedTool);
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}
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tools.push(ImageVisionTool);
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return tools.reduce((map, tool) => {
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map[tool.function.name] = tool;
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return map;
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}, {});
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}
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/**
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* Formats a `StructuredTool` instance into a format that is compatible
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* with OpenAI's ChatCompletionFunctions. It uses the `zodToJsonSchema`
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* function to convert the schema of the `StructuredTool` into a JSON
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* schema, which is then used as the parameters for the OpenAI function.
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*
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* @param {StructuredTool} tool - The StructuredTool to format.
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* @returns {FunctionTool} The OpenAI Assistant Tool.
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*/
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function formatToOpenAIAssistantTool(tool) {
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return {
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type: Tools.function,
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[Tools.function]: {
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name: tool.name,
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description: tool.description,
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parameters: zodToJsonSchema(tool.schema),
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},
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};
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}
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/**
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* Processes the required actions by calling the appropriate tools and returning the outputs.
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* @param {OpenAIClient} client - OpenAI or StreamRunManager Client.
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* @param {RequiredAction} requiredActions - The current required action.
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* @returns {Promise<ToolOutput>} The outputs of the tools.
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*/
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const processVisionRequest = async (client, currentAction) => {
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if (!client.visionPromise) {
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return {
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tool_call_id: currentAction.toolCallId,
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output: 'No image details found.',
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};
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}
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/** @type {ChatCompletion | undefined} */
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const completion = await client.visionPromise;
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if (completion && completion.usage) {
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recordUsage({
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user: client.req.user.id,
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model: client.req.body.model,
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conversationId: (client.responseMessage ?? client.finalMessage).conversationId,
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...completion.usage,
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});
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}
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const output = completion?.choices?.[0]?.message?.content ?? 'No image details found.';
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return {
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tool_call_id: currentAction.toolCallId,
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output,
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};
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};
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/**
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* Processes return required actions from run.
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* @param {OpenAIClient | StreamRunManager} client - OpenAI (legacy) or StreamRunManager Client.
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* @param {RequiredAction[]} requiredActions - The required actions to submit outputs for.
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* @returns {Promise<ToolOutputs>} The outputs of the tools.
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*/
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async function processRequiredActions(client, requiredActions) {
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logger.debug(
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`[required actions] user: ${client.req.user.id} | thread_id: ${requiredActions[0].thread_id} | run_id: ${requiredActions[0].run_id}`,
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requiredActions,
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);
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const tools = requiredActions.map((action) => action.tool);
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const { loadedTools } = await loadTools({
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user: client.req.user.id,
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model: client.req.body.model ?? 'gpt-4o-mini',
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tools,
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functions: true,
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endpoint: client.req.body.endpoint,
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options: {
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processFileURL,
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req: client.req,
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uploadImageBuffer,
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openAIApiKey: client.apiKey,
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fileStrategy: client.req.app.locals.fileStrategy,
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returnMetadata: true,
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},
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});
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const ToolMap = loadedTools.reduce((map, tool) => {
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map[tool.name] = tool;
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return map;
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}, {});
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const promises = [];
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/** @type {Action[]} */
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let actionSets = [];
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let isActionTool = false;
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const ActionToolMap = {};
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const ActionBuildersMap = {};
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for (let i = 0; i < requiredActions.length; i++) {
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const currentAction = requiredActions[i];
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if (currentAction.tool === ImageVisionTool.function.name) {
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promises.push(processVisionRequest(client, currentAction));
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continue;
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}
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let tool = ToolMap[currentAction.tool] ?? ActionToolMap[currentAction.tool];
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const handleToolOutput = async (output) => {
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requiredActions[i].output = output;
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/** @type {FunctionToolCall & PartMetadata} */
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const toolCall = {
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function: {
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name: currentAction.tool,
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arguments: JSON.stringify(currentAction.toolInput),
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output,
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},
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id: currentAction.toolCallId,
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type: 'function',
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progress: 1,
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action: isActionTool,
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};
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const toolCallIndex = client.mappedOrder.get(toolCall.id);
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if (imageGenTools.has(currentAction.tool)) {
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const imageOutput = output;
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toolCall.function.output = `${currentAction.tool} displayed an image. All generated images are already plainly visible, so don't repeat the descriptions in detail. Do not list download links as they are available in the UI already. The user may download the images by clicking on them, but do not mention anything about downloading to the user.`;
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// Streams the "Finished" state of the tool call in the UI
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client.addContentData({
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[ContentTypes.TOOL_CALL]: toolCall,
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index: toolCallIndex,
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type: ContentTypes.TOOL_CALL,
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});
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await sleep(500);
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/** @type {ImageFile} */
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const imageDetails = {
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...imageOutput,
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...currentAction.toolInput,
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};
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const image_file = {
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[ContentTypes.IMAGE_FILE]: imageDetails,
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type: ContentTypes.IMAGE_FILE,
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// Replace the tool call output with Image file
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index: toolCallIndex,
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};
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client.addContentData(image_file);
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// Update the stored tool call
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client.seenToolCalls && client.seenToolCalls.set(toolCall.id, toolCall);
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return {
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tool_call_id: currentAction.toolCallId,
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output: toolCall.function.output,
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};
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}
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client.seenToolCalls && client.seenToolCalls.set(toolCall.id, toolCall);
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client.addContentData({
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[ContentTypes.TOOL_CALL]: toolCall,
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index: toolCallIndex,
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type: ContentTypes.TOOL_CALL,
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// TODO: to append tool properties to stream, pass metadata rest to addContentData
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// result: tool.result,
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});
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return {
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tool_call_id: currentAction.toolCallId,
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output,
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};
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};
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if (!tool) {
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// throw new Error(`Tool ${currentAction.tool} not found.`);
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if (!actionSets.length) {
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actionSets =
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(await loadActionSets({
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assistant_id: client.req.body.assistant_id,
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})) ?? [];
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}
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let actionSet = null;
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let currentDomain = '';
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for (let action of actionSets) {
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const domain = await domainParser(client.req, action.metadata.domain, true);
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if (currentAction.tool.includes(domain)) {
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currentDomain = domain;
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actionSet = action;
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break;
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}
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}
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if (!actionSet) {
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// TODO: try `function` if no action set is found
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// throw new Error(`Tool ${currentAction.tool} not found.`);
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continue;
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}
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let builders = ActionBuildersMap[actionSet.metadata.domain];
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if (!builders) {
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const validationResult = validateAndParseOpenAPISpec(actionSet.metadata.raw_spec);
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if (!validationResult.spec) {
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throw new Error(
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`Invalid spec: user: ${client.req.user.id} | thread_id: ${requiredActions[0].thread_id} | run_id: ${requiredActions[0].run_id}`,
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);
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}
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const { requestBuilders } = openapiToFunction(validationResult.spec);
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ActionToolMap[actionSet.metadata.domain] = requestBuilders;
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builders = requestBuilders;
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}
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const functionName = currentAction.tool.replace(`${actionDelimiter}${currentDomain}`, '');
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const requestBuilder = builders[functionName];
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if (!requestBuilder) {
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// throw new Error(`Tool ${currentAction.tool} not found.`);
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continue;
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}
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tool = await createActionTool({ action: actionSet, requestBuilder });
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if (!tool) {
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logger.warn(
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`Invalid action: user: ${client.req.user.id} | thread_id: ${requiredActions[0].thread_id} | run_id: ${requiredActions[0].run_id} | toolName: ${currentAction.tool}`,
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);
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throw new Error(`{"type":"${ErrorTypes.INVALID_ACTION}"}`);
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}
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isActionTool = !!tool;
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ActionToolMap[currentAction.tool] = tool;
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}
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if (currentAction.tool === 'calculator') {
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currentAction.toolInput = currentAction.toolInput.input;
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}
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const handleToolError = (error) => {
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logger.error(
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`tool_call_id: ${currentAction.toolCallId} | Error processing tool ${currentAction.tool}`,
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error,
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);
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return {
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tool_call_id: currentAction.toolCallId,
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output: `Error processing tool ${currentAction.tool}: ${redactMessage(error.message, 256)}`,
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};
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};
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try {
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const promise = tool
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._call(currentAction.toolInput)
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.then(handleToolOutput)
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.catch(handleToolError);
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promises.push(promise);
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} catch (error) {
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const toolOutputError = handleToolError(error);
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promises.push(Promise.resolve(toolOutputError));
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}
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}
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return {
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tool_outputs: await Promise.all(promises),
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};
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}
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/**
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* Processes the runtime tool calls and returns the tool classes.
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* @param {Object} params - Run params containing user and request information.
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* @param {ServerRequest} params.req - The request object.
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* @param {Agent} params.agent - The agent to load tools for.
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* @param {string | undefined} [params.openAIApiKey] - The OpenAI API key.
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* @returns {Promise<{ tools?: StructuredTool[] }>} The agent tools.
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*/
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async function loadAgentTools({ req, agent, tool_resources, openAIApiKey }) {
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if (!agent.tools || agent.tools.length === 0) {
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return {};
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}
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const { loadedTools, toolContextMap } = await loadTools({
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agent,
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functions: true,
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user: req.user.id,
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tools: agent.tools,
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options: {
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req,
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openAIApiKey,
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tool_resources,
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processFileURL,
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uploadImageBuffer,
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returnMetadata: true,
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fileStrategy: req.app.locals.fileStrategy,
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},
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});
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const agentTools = [];
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for (let i = 0; i < loadedTools.length; i++) {
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const tool = loadedTools[i];
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if (tool.name && (tool.name === Tools.execute_code || tool.name === Tools.file_search)) {
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agentTools.push(tool);
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continue;
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}
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if (tool.mcp === true) {
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agentTools.push(tool);
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continue;
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}
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const toolDefinition = {
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name: tool.name,
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schema: tool.schema,
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description: tool.description,
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};
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if (imageGenTools.has(tool.name)) {
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toolDefinition.responseFormat = 'content_and_artifact';
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}
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const toolInstance = toolFn(async (...args) => {
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return tool['_call'](...args);
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}, toolDefinition);
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agentTools.push(toolInstance);
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}
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const ToolMap = loadedTools.reduce((map, tool) => {
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map[tool.name] = tool;
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return map;
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}, {});
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let actionSets = [];
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const ActionToolMap = {};
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for (const toolName of agent.tools) {
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if (!ToolMap[toolName]) {
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if (!actionSets.length) {
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actionSets = (await loadActionSets({ agent_id: agent.id })) ?? [];
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}
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let actionSet = null;
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let currentDomain = '';
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for (let action of actionSets) {
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const domain = await domainParser(req, action.metadata.domain, true);
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if (toolName.includes(domain)) {
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currentDomain = domain;
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actionSet = action;
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break;
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}
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}
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|
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if (actionSet) {
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const validationResult = validateAndParseOpenAPISpec(actionSet.metadata.raw_spec);
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if (validationResult.spec) {
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const { requestBuilders, functionSignatures, zodSchemas } = openapiToFunction(
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validationResult.spec,
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true,
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);
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const functionName = toolName.replace(`${actionDelimiter}${currentDomain}`, '');
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const functionSig = functionSignatures.find((sig) => sig.name === functionName);
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const requestBuilder = requestBuilders[functionName];
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const zodSchema = zodSchemas[functionName];
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if (requestBuilder) {
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const tool = await createActionTool({
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action: actionSet,
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requestBuilder,
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zodSchema,
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name: toolName,
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description: functionSig.description,
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});
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if (!tool) {
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logger.warn(
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|
`Invalid action: user: ${req.user.id} | agent_id: ${agent.id} | toolName: ${toolName}`,
|
|
);
|
|
throw new Error(`{"type":"${ErrorTypes.INVALID_ACTION}"}`);
|
|
}
|
|
agentTools.push(tool);
|
|
ActionToolMap[toolName] = tool;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if (agent.tools.length > 0 && agentTools.length === 0) {
|
|
throw new Error('No tools found for the specified tool calls.');
|
|
}
|
|
|
|
return {
|
|
tools: agentTools,
|
|
toolContextMap,
|
|
};
|
|
}
|
|
|
|
module.exports = {
|
|
loadAgentTools,
|
|
loadAndFormatTools,
|
|
processRequiredActions,
|
|
formatToOpenAIAssistantTool,
|
|
};
|