mirror of
https://github.com/danny-avila/LibreChat.git
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* WIP: code ptc
* refactor: tool classification and calling logic
* 🔧 fix: Update @librechat/agents dependency to version 3.0.68
* chore: import order and correct renamed tool name for tool search
* refactor: streamline tool classification logic for local and programmatic tools
* feat: add per-tool configuration options for agents, including deferred loading and allowed callers
- Introduced `tool_options` in agent forms to manage tool behavior.
- Updated tool classification logic to prioritize agent-level configurations.
- Enhanced UI components to support tool deferral functionality.
- Added localization strings for new tool options and actions.
* feat: enhance agent schema with per-tool options for configuration
- Added `tool_options` schema to support per-tool configurations, including `defer_loading` and `allowed_callers`.
- Updated agent data model to incorporate new tool options, ensuring flexibility in tool behavior management.
- Modified type definitions to reflect the new `tool_options` structure for agents.
* feat: add tool_options parameter to loadTools and initializeAgent for enhanced agent configuration
* chore: update @librechat/agents dependency to version 3.0.71 and enhance agent tool loading logic
- Updated the @librechat/agents package to version 3.0.71 across multiple files.
- Added support for handling deferred loading of tools in agent initialization and execution processes.
- Improved the extraction of discovered tools from message history to optimize tool loading behavior.
* chore: update @librechat/agents dependency to version 3.0.72
* chore: update @librechat/agents dependency to version 3.0.75
* refactor: simplify tool defer loading logic in MCPTool component
- Removed local state management for deferred tools, relying on form state instead.
- Updated related functions to directly use form values for checking and toggling defer loading.
- Cleaned up code by eliminating unnecessary optimistic updates and local state dependencies.
* chore: remove deprecated localization strings for tool deferral in translation.json
- Eliminated unused strings related to deferred loading descriptions in the English translation file.
- Streamlined localization to reflect recent changes in tool loading logic.
* refactor: improve tool defer loading handling in MCPTool component
- Enhanced the logic for managing deferred loading of tools by simplifying the update process for tool options.
- Ensured that the state reflects the correct loading behavior based on the new deferred loading conditions.
- Cleaned up the code to remove unnecessary complexity in handling tool options.
* refactor: update agent mocks in callbacks test to use actual implementations
- Modified the agent mocks in the callbacks test to include actual implementations from the @librechat/agents module.
- This change enhances the accuracy of the tests by ensuring they reflect the real behavior of the agent functions.
326 lines
10 KiB
TypeScript
326 lines
10 KiB
TypeScript
import { Run, Providers } from '@librechat/agents';
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import { providerEndpointMap, KnownEndpoints } from 'librechat-data-provider';
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import type { BaseMessage } from '@langchain/core/messages';
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import type {
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MultiAgentGraphConfig,
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OpenAIClientOptions,
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StandardGraphConfig,
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LCToolRegistry,
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AgentInputs,
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GenericTool,
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RunConfig,
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IState,
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} from '@librechat/agents';
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import type { IUser } from '@librechat/data-schemas';
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import type { Agent } from 'librechat-data-provider';
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import type * as t from '~/types';
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import { resolveHeaders, createSafeUser } from '~/utils/env';
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/** Tool search tool name constant */
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const TOOL_SEARCH_NAME = 'tool_search';
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/** Expected shape of JSON tool search results */
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interface ToolSearchJsonResult {
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found?: number;
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tools?: Array<{ name: string }>;
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}
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/**
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* Parses tool names from JSON-formatted tool_search output.
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* Format: { "found": N, "tools": [{ "name": "tool_name", ... }], ... }
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*
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* @param content - The JSON string content
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* @param discoveredTools - Set to add discovered tool names to
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* @returns true if parsing succeeded, false otherwise
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*/
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function parseToolSearchJson(content: string, discoveredTools: Set<string>): boolean {
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try {
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const parsed = JSON.parse(content) as ToolSearchJsonResult;
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if (!parsed.tools || !Array.isArray(parsed.tools)) {
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return false;
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}
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for (const tool of parsed.tools) {
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if (tool.name && typeof tool.name === 'string') {
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discoveredTools.add(tool.name);
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}
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}
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return parsed.tools.length > 0;
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} catch {
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return false;
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}
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}
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/**
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* Parses tool names from legacy text-formatted tool_search output.
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* Format: "- tool_name (score: X.XX)"
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*
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* @param content - The text content
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* @param discoveredTools - Set to add discovered tool names to
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*/
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function parseToolSearchLegacy(content: string, discoveredTools: Set<string>): void {
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const toolNameRegex = /^- ([^\s(]+)\s*\(score:/gm;
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let match: RegExpExecArray | null;
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while ((match = toolNameRegex.exec(content)) !== null) {
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const toolName = match[1];
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if (toolName) {
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discoveredTools.add(toolName);
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}
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}
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}
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/**
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* Extracts discovered tool names from message history by parsing tool_search results.
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* When the LLM calls tool_search, the result contains tool names that were discovered.
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* These tools should have defer_loading overridden to false on subsequent turns.
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*
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* Supports both:
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* - New JSON format: { "tools": [{ "name": "tool_name" }] }
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* - Legacy text format: "- tool_name (score: X.XX)"
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*
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* @param messages - The conversation message history
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* @returns Set of tool names that were discovered via tool_search
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*/
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export function extractDiscoveredToolsFromHistory(messages: BaseMessage[]): Set<string> {
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const discoveredTools = new Set<string>();
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for (const message of messages) {
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const msgType = message._getType?.() ?? message.constructor?.name ?? '';
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if (msgType !== 'tool') {
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continue;
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}
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const name = (message as { name?: string }).name;
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if (name !== TOOL_SEARCH_NAME) {
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continue;
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}
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const content = message.content;
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if (typeof content !== 'string') {
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continue;
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}
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/** Try JSON format first (new), fall back to regex (legacy) */
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if (!parseToolSearchJson(content, discoveredTools)) {
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parseToolSearchLegacy(content, discoveredTools);
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}
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}
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return discoveredTools;
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}
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/**
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* Overrides defer_loading to false for tools that were already discovered via tool_search.
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* This prevents the LLM from having to re-discover tools on every turn.
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*
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* @param toolRegistry - The tool registry to modify (mutated in place)
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* @param discoveredTools - Set of tool names that were previously discovered
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* @returns Number of tools that had defer_loading overridden
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*/
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export function overrideDeferLoadingForDiscoveredTools(
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toolRegistry: LCToolRegistry,
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discoveredTools: Set<string>,
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): number {
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let overrideCount = 0;
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for (const toolName of discoveredTools) {
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const toolDef = toolRegistry.get(toolName);
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if (toolDef && toolDef.defer_loading === true) {
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toolDef.defer_loading = false;
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overrideCount++;
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}
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}
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return overrideCount;
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}
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const customProviders = new Set([
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Providers.XAI,
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Providers.DEEPSEEK,
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Providers.OPENROUTER,
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KnownEndpoints.ollama,
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]);
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export function getReasoningKey(
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provider: Providers,
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llmConfig: t.RunLLMConfig,
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agentEndpoint?: string | null,
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): 'reasoning_content' | 'reasoning' {
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let reasoningKey: 'reasoning_content' | 'reasoning' = 'reasoning_content';
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if (provider === Providers.GOOGLE) {
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reasoningKey = 'reasoning';
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} else if (
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llmConfig.configuration?.baseURL?.includes(KnownEndpoints.openrouter) ||
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(agentEndpoint && agentEndpoint.toLowerCase().includes(KnownEndpoints.openrouter))
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) {
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reasoningKey = 'reasoning';
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} else if (
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(llmConfig as OpenAIClientOptions).useResponsesApi === true &&
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(provider === Providers.OPENAI || provider === Providers.AZURE)
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) {
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reasoningKey = 'reasoning';
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}
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return reasoningKey;
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}
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type RunAgent = Omit<Agent, 'tools'> & {
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tools?: GenericTool[];
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maxContextTokens?: number;
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useLegacyContent?: boolean;
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toolContextMap?: Record<string, string>;
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toolRegistry?: LCToolRegistry;
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/** Precomputed flag indicating if any tools have defer_loading enabled */
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hasDeferredTools?: boolean;
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};
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/**
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* Creates a new Run instance with custom handlers and configuration.
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*
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* @param options - The options for creating the Run instance.
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* @param options.agents - The agents for this run.
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* @param options.signal - The signal for this run.
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* @param options.runId - Optional run ID; otherwise, a new run ID will be generated.
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* @param options.customHandlers - Custom event handlers.
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* @param options.streaming - Whether to use streaming.
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* @param options.streamUsage - Whether to stream usage information.
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* @param options.messages - Optional message history to extract discovered tools from.
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* When provided, tools that were previously discovered via tool_search will have
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* their defer_loading overridden to false, preventing redundant re-discovery.
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* @returns {Promise<Run<IState>>} A promise that resolves to a new Run instance.
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*/
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export async function createRun({
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runId,
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signal,
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agents,
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messages,
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requestBody,
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user,
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tokenCounter,
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customHandlers,
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indexTokenCountMap,
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streaming = true,
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streamUsage = true,
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}: {
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agents: RunAgent[];
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signal: AbortSignal;
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runId?: string;
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streaming?: boolean;
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streamUsage?: boolean;
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requestBody?: t.RequestBody;
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user?: IUser;
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/** Message history for extracting previously discovered tools */
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messages?: BaseMessage[];
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} & Pick<RunConfig, 'tokenCounter' | 'customHandlers' | 'indexTokenCountMap'>): Promise<
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Run<IState>
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> {
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/**
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* Only extract discovered tools if:
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* 1. We have message history to parse
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* 2. At least one agent has deferred tools (using precomputed flag)
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*
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* This optimization avoids iterating through messages in the ~95% of cases
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* where no agent uses deferred tool loading.
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*/
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const hasAnyDeferredTools = agents.some((agent) => agent.hasDeferredTools === true);
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const discoveredTools =
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hasAnyDeferredTools && messages?.length
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? extractDiscoveredToolsFromHistory(messages)
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: new Set<string>();
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const agentInputs: AgentInputs[] = [];
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const buildAgentContext = (agent: RunAgent) => {
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const provider =
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(providerEndpointMap[
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agent.provider as keyof typeof providerEndpointMap
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] as unknown as Providers) ?? agent.provider;
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const llmConfig: t.RunLLMConfig = Object.assign(
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{
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provider,
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streaming,
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streamUsage,
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},
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agent.model_parameters,
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);
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const systemMessage = Object.values(agent.toolContextMap ?? {})
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.join('\n')
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.trim();
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const systemContent = [
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systemMessage,
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agent.instructions ?? '',
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agent.additional_instructions ?? '',
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]
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.join('\n')
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.trim();
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/**
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* Resolve request-based headers for Custom Endpoints. Note: if this is added to
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* non-custom endpoints, needs consideration of varying provider header configs.
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* This is done at this step because the request body may contain dynamic values
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* that need to be resolved after agent initialization.
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*/
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if (llmConfig?.configuration?.defaultHeaders != null) {
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llmConfig.configuration.defaultHeaders = resolveHeaders({
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headers: llmConfig.configuration.defaultHeaders as Record<string, string>,
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user: createSafeUser(user),
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body: requestBody,
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});
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}
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/** Resolves issues with new OpenAI usage field */
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if (
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customProviders.has(agent.provider) ||
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(agent.provider === Providers.OPENAI && agent.endpoint !== agent.provider)
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) {
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llmConfig.streamUsage = false;
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llmConfig.usage = true;
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}
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/**
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* Override defer_loading for tools that were discovered in previous turns.
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* This prevents the LLM from having to re-discover tools via tool_search.
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*/
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if (discoveredTools.size > 0 && agent.toolRegistry) {
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overrideDeferLoadingForDiscoveredTools(agent.toolRegistry, discoveredTools);
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}
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const reasoningKey = getReasoningKey(provider, llmConfig, agent.endpoint);
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const agentInput: AgentInputs = {
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provider,
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reasoningKey,
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agentId: agent.id,
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name: agent.name ?? undefined,
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tools: agent.tools,
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clientOptions: llmConfig,
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instructions: systemContent,
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toolRegistry: agent.toolRegistry,
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maxContextTokens: agent.maxContextTokens,
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useLegacyContent: agent.useLegacyContent ?? false,
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};
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agentInputs.push(agentInput);
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};
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for (const agent of agents) {
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buildAgentContext(agent);
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}
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const graphConfig: RunConfig['graphConfig'] = {
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signal,
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agents: agentInputs,
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edges: agents[0].edges,
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};
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if (agentInputs.length > 1 || ((graphConfig as MultiAgentGraphConfig).edges?.length ?? 0) > 0) {
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(graphConfig as unknown as MultiAgentGraphConfig).type = 'multi-agent';
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} else {
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(graphConfig as StandardGraphConfig).type = 'standard';
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}
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return Run.create({
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runId,
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graphConfig,
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tokenCounter,
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customHandlers,
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indexTokenCountMap,
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});
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}
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