mirror of
https://github.com/danny-avila/LibreChat.git
synced 2026-01-16 15:35:31 +01:00
* 🌊 feat: Implement multi-conversation feature with added conversation context and payload adjustments
* refactor: Replace isSubmittingFamily with isSubmitting across message components for consistency
* feat: Add loadAddedAgent and processAddedConvo for multi-conversation agent execution
* refactor: Update ContentRender usage to conditionally render PlaceholderRow based on isLast and isSubmitting
* WIP: first pass, sibling index
* feat: Enhance multi-conversation support with agent tracking and display improvements
* refactor: Introduce isEphemeralAgentId utility and update related logic for agent handling
* refactor: Implement createDualMessageContent utility for sibling message display and enhance useStepHandler for added conversations
* refactor: duplicate tools for added agent if ephemeral and primary agent is also ephemeral
* chore: remove deprecated multimessage rendering
* refactor: enhance dual message content creation and agent handling for parallel rendering
* refactor: streamline message rendering and submission handling by removing unused state and optimizing conditional logic
* refactor: adjust content handling in parallel mode to utilize existing content for improved agent display
* refactor: update @librechat/agents dependency to version 3.0.53
* refactor: update @langchain/core and @librechat/agents dependencies to latest versions
* refactor: remove deprecated @langchain/core dependency from package.json
* chore: remove unused SearchToolConfig and GetSourcesParams types from web.ts
* refactor: remove unused message properties from Message component
* refactor: enhance parallel content handling with groupId support in ContentParts and useStepHandler
* refactor: implement parallel content styling in Message, MessageRender, and ContentRender components. use explicit model name
* refactor: improve agent ID handling in createDualMessageContent for dual message display
* refactor: simplify title generation in AddedConvo by removing unused sender and preset logic
* refactor: replace string interpolation with cn utility for className in HoverButtons component
* refactor: enhance agent ID handling by adding suffix management for parallel agents and updating related components
* refactor: enhance column ordering in ContentParts by sorting agents with suffix management
* refactor: update @librechat/agents dependency to version 3.0.55
* feat: implement parallel content rendering with metadata support
- Added `ParallelContentRenderer` and `ParallelColumns` components for rendering messages in parallel based on groupId and agentId.
- Introduced `contentMetadataMap` to store metadata for each content part, allowing efficient parallel content detection.
- Updated `Message` and `ContentRender` components to utilize the new metadata structure for rendering.
- Modified `useStepHandler` to manage content indices and metadata during message processing.
- Enhanced `IJobStore` interface and its implementations to support storing and retrieving content metadata.
- Updated data schemas to include `contentMetadataMap` for messages, enabling multi-agent and parallel execution scenarios.
* refactor: update @librechat/agents dependency to version 3.0.56
* refactor: remove unused EPHEMERAL_AGENT_ID constant and simplify agent ID check
* refactor: enhance multi-agent message processing and primary agent determination
* refactor: implement branch message functionality for parallel responses
* refactor: integrate added conversation retrieval into message editing and regeneration processes
* refactor: remove unused isCard and isMultiMessage props from MessageRender and ContentRender components
* refactor: update @librechat/agents dependency to version 3.0.60
* refactor: replace usage of EPHEMERAL_AGENT_ID constant with isEphemeralAgentId function for improved clarity and consistency
* refactor: standardize agent ID format in tests for consistency
* chore: move addedConvo property to the correct position in payload construction
* refactor: rename agent_id values in loadAgent tests for clarity
* chore: reorder props in ContentParts component for improved readability
* refactor: rename variable 'content' to 'result' for clarity in RedisJobStore tests
* refactor: streamline useMessageActions by removing duplicate handleFeedback assignment
* chore: revert placeholder rendering logic MessageRender and ContentRender components to original
* refactor: implement useContentMetadata hook for optimized content metadata handling
* refactor: remove contentMetadataMap and related logic from the codebase and revert back to agentId/groupId in content parts
- Eliminated contentMetadataMap from various components and services, simplifying the handling of message content.
- Updated functions to directly access agentId and groupId from content parts instead of relying on a separate metadata map.
- Adjusted related hooks and components to reflect the removal of contentMetadataMap, ensuring consistent handling of message content.
- Updated tests and documentation to align with the new structure of message content handling.
* refactor: remove logging from groupParallelContent function to clean up output
* refactor: remove model parameter from TBranchMessageRequest type for simplification
* refactor: enhance branch message creation by stripping metadata for standalone content
* chore: streamline branch message creation by simplifying content filtering and removing unnecessary metadata checks
* refactor: include attachments in branch message creation for improved content handling
* refactor: streamline agent content processing by consolidating primary agent identification and filtering logic
* refactor: simplify multi-agent message processing by creating a dedicated mapping method and enhancing content filtering
* refactor: remove unused parameter from loadEphemeralAgent function for cleaner code
* refactor: update groupId handling in metadata to only set when provided by the server
553 lines
16 KiB
TypeScript
553 lines
16 KiB
TypeScript
import dayjs from 'dayjs';
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import type { ZodIssue } from 'zod';
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import type * as a from './types/assistants';
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import type * as s from './schemas';
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import type * as t from './types';
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import { ContentTypes } from './types/runs';
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import {
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openAISchema,
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googleSchema,
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EModelEndpoint,
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anthropicSchema,
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assistantSchema,
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// agentsSchema,
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compactAgentsSchema,
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compactGoogleSchema,
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compactAssistantSchema,
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} from './schemas';
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import { bedrockInputSchema } from './bedrock';
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import { alternateName } from './config';
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type EndpointSchema =
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| typeof openAISchema
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| typeof googleSchema
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| typeof anthropicSchema
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| typeof assistantSchema
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| typeof compactAgentsSchema
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| typeof bedrockInputSchema;
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export type EndpointSchemaKey = EModelEndpoint;
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const endpointSchemas: Record<EndpointSchemaKey, EndpointSchema> = {
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[EModelEndpoint.openAI]: openAISchema,
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[EModelEndpoint.azureOpenAI]: openAISchema,
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[EModelEndpoint.custom]: openAISchema,
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[EModelEndpoint.google]: googleSchema,
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[EModelEndpoint.anthropic]: anthropicSchema,
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[EModelEndpoint.assistants]: assistantSchema,
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[EModelEndpoint.azureAssistants]: assistantSchema,
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[EModelEndpoint.agents]: compactAgentsSchema,
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[EModelEndpoint.bedrock]: bedrockInputSchema,
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};
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// const schemaCreators: Record<EModelEndpoint, (customSchema: DefaultSchemaValues) => EndpointSchema> = {
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// [EModelEndpoint.google]: createGoogleSchema,
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// };
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/** Get the enabled endpoints from the `ENDPOINTS` environment variable */
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export function getEnabledEndpoints() {
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const defaultEndpoints: string[] = [
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EModelEndpoint.openAI,
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EModelEndpoint.agents,
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EModelEndpoint.assistants,
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EModelEndpoint.azureAssistants,
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EModelEndpoint.azureOpenAI,
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EModelEndpoint.google,
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EModelEndpoint.anthropic,
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EModelEndpoint.bedrock,
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];
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const endpointsEnv = process.env.ENDPOINTS ?? '';
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let enabledEndpoints = defaultEndpoints;
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if (endpointsEnv) {
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enabledEndpoints = endpointsEnv
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.split(',')
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.filter((endpoint) => endpoint.trim())
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.map((endpoint) => endpoint.trim());
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}
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return enabledEndpoints;
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}
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/** Orders an existing EndpointsConfig object based on enabled endpoint/custom ordering */
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export function orderEndpointsConfig(endpointsConfig: t.TEndpointsConfig) {
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if (!endpointsConfig) {
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return {};
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}
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const enabledEndpoints = getEnabledEndpoints();
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const endpointKeys = Object.keys(endpointsConfig);
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const defaultCustomIndex = enabledEndpoints.indexOf(EModelEndpoint.custom);
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return endpointKeys.reduce(
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(accumulatedConfig: Record<string, t.TConfig | null | undefined>, currentEndpointKey) => {
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const isCustom = !(currentEndpointKey in EModelEndpoint);
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const isEnabled = enabledEndpoints.includes(currentEndpointKey);
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if (!isEnabled && !isCustom) {
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return accumulatedConfig;
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}
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const index = enabledEndpoints.indexOf(currentEndpointKey);
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if (isCustom) {
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accumulatedConfig[currentEndpointKey] = {
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order: defaultCustomIndex >= 0 ? defaultCustomIndex : 9999,
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...(endpointsConfig[currentEndpointKey] as Omit<t.TConfig, 'order'> & { order?: number }),
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};
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} else if (endpointsConfig[currentEndpointKey]) {
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accumulatedConfig[currentEndpointKey] = {
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...endpointsConfig[currentEndpointKey],
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order: index,
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};
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}
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return accumulatedConfig;
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},
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{},
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);
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}
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/** Converts an array of Zod issues into a string. */
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export function errorsToString(errors: ZodIssue[]) {
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return errors
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.map((error) => {
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const field = error.path.join('.');
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const message = error.message;
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return `${field}: ${message}`;
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})
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.join(' ');
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}
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export function getFirstDefinedValue(possibleValues: string[]) {
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let returnValue;
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for (const value of possibleValues) {
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if (value) {
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returnValue = value;
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break;
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}
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}
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return returnValue;
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}
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export function getNonEmptyValue(possibleValues: string[]) {
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for (const value of possibleValues) {
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if (value && value.trim() !== '') {
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return value;
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}
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}
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return undefined;
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}
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export type TPossibleValues = {
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models: string[];
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};
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export const parseConvo = ({
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endpoint,
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endpointType,
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conversation,
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possibleValues,
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}: {
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endpoint: EndpointSchemaKey;
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endpointType?: EndpointSchemaKey | null;
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conversation: Partial<s.TConversation | s.TPreset> | null;
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possibleValues?: TPossibleValues;
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// TODO: POC for default schema
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// defaultSchema?: Partial<EndpointSchema>,
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}) => {
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let schema = endpointSchemas[endpoint] as EndpointSchema | undefined;
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if (!schema && !endpointType) {
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throw new Error(`Unknown endpoint: ${endpoint}`);
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} else if (!schema && endpointType) {
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schema = endpointSchemas[endpointType];
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}
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// if (defaultSchema && schemaCreators[endpoint]) {
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// schema = schemaCreators[endpoint](defaultSchema);
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// }
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const convo = schema?.parse(conversation) as s.TConversation | undefined;
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const { models } = possibleValues ?? {};
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if (models && convo) {
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convo.model = getFirstDefinedValue(models) ?? convo.model;
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}
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return convo;
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};
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/** Match GPT followed by digit, optional decimal, and optional suffix
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*
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* Examples: gpt-4, gpt-4o, gpt-4.5, gpt-5a, etc. */
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const extractGPTVersion = (modelStr: string): string => {
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const gptMatch = modelStr.match(/gpt-(\d+(?:\.\d+)?)([a-z])?/i);
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if (gptMatch) {
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const version = gptMatch[1];
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const suffix = gptMatch[2] || '';
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return `GPT-${version}${suffix}`;
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}
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return '';
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};
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/** Match omni models (o1, o3, etc.), "o" followed by a digit, possibly with decimal */
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const extractOmniVersion = (modelStr: string): string => {
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const omniMatch = modelStr.match(/\bo(\d+(?:\.\d+)?)\b/i);
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if (omniMatch) {
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const version = omniMatch[1];
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return `o${version}`;
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}
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return '';
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};
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export const getResponseSender = (endpointOption: Partial<t.TEndpointOption>): string => {
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const {
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model: _m,
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endpoint: _e,
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endpointType,
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modelDisplayLabel: _mdl,
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chatGptLabel: _cgl,
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modelLabel: _ml,
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} = endpointOption;
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const endpoint = _e as EModelEndpoint;
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const model = _m ?? '';
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const modelDisplayLabel = _mdl ?? '';
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const chatGptLabel = _cgl ?? '';
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const modelLabel = _ml ?? '';
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if (
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[EModelEndpoint.openAI, EModelEndpoint.bedrock, EModelEndpoint.azureOpenAI].includes(endpoint)
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) {
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if (modelLabel) {
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return modelLabel;
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} else if (chatGptLabel) {
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// @deprecated - prefer modelLabel
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return chatGptLabel;
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} else if (model && extractOmniVersion(model)) {
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return extractOmniVersion(model);
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} else if (model && (model.includes('mistral') || model.includes('codestral'))) {
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return 'Mistral';
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} else if (model && model.includes('deepseek')) {
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return 'Deepseek';
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} else if (model && model.includes('gpt-')) {
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const gptVersion = extractGPTVersion(model);
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return gptVersion || 'GPT';
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}
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return (alternateName[endpoint] as string | undefined) ?? 'AI';
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}
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if (endpoint === EModelEndpoint.anthropic) {
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return modelLabel || 'Claude';
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}
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if (endpoint === EModelEndpoint.bedrock) {
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return modelLabel || alternateName[endpoint];
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}
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if (endpoint === EModelEndpoint.google) {
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if (modelLabel) {
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return modelLabel;
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} else if (model?.toLowerCase().includes('gemma') === true) {
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return 'Gemma';
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}
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return 'Gemini';
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}
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if (endpoint === EModelEndpoint.custom || endpointType === EModelEndpoint.custom) {
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if (modelLabel) {
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return modelLabel;
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} else if (chatGptLabel) {
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// @deprecated - prefer modelLabel
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return chatGptLabel;
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} else if (model && extractOmniVersion(model)) {
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return extractOmniVersion(model);
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} else if (model && (model.includes('mistral') || model.includes('codestral'))) {
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return 'Mistral';
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} else if (model && model.includes('deepseek')) {
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return 'Deepseek';
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} else if (model && model.includes('gpt-')) {
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const gptVersion = extractGPTVersion(model);
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return gptVersion || 'GPT';
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} else if (modelDisplayLabel) {
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return modelDisplayLabel;
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}
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return 'AI';
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}
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return '';
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};
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type CompactEndpointSchema =
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| typeof openAISchema
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| typeof compactAssistantSchema
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| typeof compactAgentsSchema
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| typeof compactGoogleSchema
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| typeof anthropicSchema
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| typeof bedrockInputSchema;
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const compactEndpointSchemas: Record<EndpointSchemaKey, CompactEndpointSchema> = {
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[EModelEndpoint.openAI]: openAISchema,
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[EModelEndpoint.azureOpenAI]: openAISchema,
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[EModelEndpoint.custom]: openAISchema,
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[EModelEndpoint.assistants]: compactAssistantSchema,
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[EModelEndpoint.azureAssistants]: compactAssistantSchema,
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[EModelEndpoint.agents]: compactAgentsSchema,
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[EModelEndpoint.google]: compactGoogleSchema,
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[EModelEndpoint.bedrock]: bedrockInputSchema,
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[EModelEndpoint.anthropic]: anthropicSchema,
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};
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export const parseCompactConvo = ({
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endpoint,
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endpointType,
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conversation,
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possibleValues,
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}: {
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endpoint?: EndpointSchemaKey;
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endpointType?: EndpointSchemaKey | null;
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conversation: Partial<s.TConversation | s.TPreset>;
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possibleValues?: TPossibleValues;
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// TODO: POC for default schema
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// defaultSchema?: Partial<EndpointSchema>,
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}): Omit<s.TConversation, 'iconURL'> | null => {
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if (!endpoint) {
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throw new Error(`undefined endpoint: ${endpoint}`);
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}
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let schema = compactEndpointSchemas[endpoint] as CompactEndpointSchema | undefined;
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if (!schema && !endpointType) {
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throw new Error(`Unknown endpoint: ${endpoint}`);
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} else if (!schema && endpointType) {
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schema = compactEndpointSchemas[endpointType];
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}
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if (!schema) {
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throw new Error(`Unknown endpointType: ${endpointType}`);
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}
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// Strip iconURL from input before parsing - it should only be derived server-side
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// from model spec configuration, not accepted from client requests
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const { iconURL: _clientIconURL, ...conversationWithoutIconURL } = conversation;
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const convo = schema.parse(conversationWithoutIconURL) as s.TConversation | null;
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const { models } = possibleValues ?? {};
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if (models && convo) {
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convo.model = getFirstDefinedValue(models) ?? convo.model;
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}
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return convo;
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};
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export function parseTextParts(
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contentParts: a.TMessageContentParts[],
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skipReasoning: boolean = false,
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): string {
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let result = '';
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for (const part of contentParts) {
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if (!part.type) {
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continue;
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}
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if (part.type === ContentTypes.TEXT) {
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const textValue = (typeof part.text === 'string' ? part.text : part.text?.value) || '';
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if (
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result.length > 0 &&
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textValue.length > 0 &&
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result[result.length - 1] !== ' ' &&
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textValue[0] !== ' '
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) {
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result += ' ';
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}
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result += textValue;
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} else if (part.type === ContentTypes.THINK && !skipReasoning) {
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const textValue = typeof part.think === 'string' ? part.think : '';
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if (
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result.length > 0 &&
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textValue.length > 0 &&
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result[result.length - 1] !== ' ' &&
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textValue[0] !== ' '
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) {
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result += ' ';
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}
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result += textValue;
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}
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}
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return result;
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}
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export const SEPARATORS = ['.', '?', '!', '۔', '。', '‥', ';', '¡', '¿', '\n', '```'];
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export function findLastSeparatorIndex(text: string, separators = SEPARATORS): number {
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let lastIndex = -1;
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for (const separator of separators) {
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const index = text.lastIndexOf(separator);
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if (index > lastIndex) {
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lastIndex = index;
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}
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}
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return lastIndex;
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}
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export function replaceSpecialVars({ text, user }: { text: string; user?: t.TUser | null }) {
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let result = text;
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if (!result) {
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return result;
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}
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// e.g., "2024-04-29 (1)" (1=Monday)
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const currentDate = dayjs().format('YYYY-MM-DD');
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const dayNumber = dayjs().day();
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const combinedDate = `${currentDate} (${dayNumber})`;
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result = result.replace(/{{current_date}}/gi, combinedDate);
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const currentDatetime = dayjs().format('YYYY-MM-DD HH:mm:ss');
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result = result.replace(/{{current_datetime}}/gi, `${currentDatetime} (${dayNumber})`);
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const isoDatetime = dayjs().toISOString();
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result = result.replace(/{{iso_datetime}}/gi, isoDatetime);
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if (user && user.name) {
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result = result.replace(/{{current_user}}/gi, user.name);
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}
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return result;
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}
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/**
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* Parsed ephemeral agent ID result
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*/
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export type ParsedEphemeralAgentId = {
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endpoint: string;
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model: string;
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sender?: string;
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index?: number;
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};
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/**
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* Encodes an ephemeral agent ID from endpoint, model, optional sender, and optional index.
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* Uses __ to replace : (reserved in graph node names) and ___ to separate sender.
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*
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* Format: endpoint__model___sender or endpoint__model___sender____index (if index provided)
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*
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* @example
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* encodeEphemeralAgentId({ endpoint: 'openAI', model: 'gpt-4o', sender: 'GPT-4o' })
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* // => 'openAI__gpt-4o___GPT-4o'
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*
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* @example
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* encodeEphemeralAgentId({ endpoint: 'openAI', model: 'gpt-4o', sender: 'GPT-4o', index: 1 })
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* // => 'openAI__gpt-4o___GPT-4o____1'
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*/
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export function encodeEphemeralAgentId({
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endpoint,
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model,
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sender,
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index,
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}: {
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endpoint: string;
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model: string;
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sender?: string;
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index?: number;
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}): string {
|
||
const base = `${endpoint}:${model}`.replace(/:/g, '__');
|
||
let result = base;
|
||
if (sender) {
|
||
// Use ___ as separator before sender to distinguish from __ in model names
|
||
result = `${base}___${sender.replace(/:/g, '__')}`;
|
||
}
|
||
if (index != null) {
|
||
// Use ____ (4 underscores) as separator for index
|
||
result = `${result}____${index}`;
|
||
}
|
||
return result;
|
||
}
|
||
|
||
/**
|
||
* Parses an ephemeral agent ID back into its components.
|
||
* Returns undefined if the ID doesn't match the expected format.
|
||
*
|
||
* Format: endpoint__model___sender or endpoint__model___sender____index
|
||
* - ____ (4 underscores) separates optional index suffix
|
||
* - ___ (triple underscore) separates model from optional sender
|
||
* - __ (double underscore) replaces : in endpoint/model names
|
||
*
|
||
* @example
|
||
* parseEphemeralAgentId('openAI__gpt-4o___GPT-4o')
|
||
* // => { endpoint: 'openAI', model: 'gpt-4o', sender: 'GPT-4o' }
|
||
*
|
||
* @example
|
||
* parseEphemeralAgentId('openAI__gpt-4o___GPT-4o____1')
|
||
* // => { endpoint: 'openAI', model: 'gpt-4o', sender: 'GPT-4o', index: 1 }
|
||
*/
|
||
export function parseEphemeralAgentId(agentId: string): ParsedEphemeralAgentId | undefined {
|
||
if (!agentId.includes('__')) {
|
||
return undefined;
|
||
}
|
||
|
||
// First check for index suffix (separated by ____)
|
||
let index: number | undefined;
|
||
let workingId = agentId;
|
||
if (agentId.includes('____')) {
|
||
const lastIndexSep = agentId.lastIndexOf('____');
|
||
const indexStr = agentId.slice(lastIndexSep + 4);
|
||
const parsedIndex = parseInt(indexStr, 10);
|
||
if (!isNaN(parsedIndex)) {
|
||
index = parsedIndex;
|
||
workingId = agentId.slice(0, lastIndexSep);
|
||
}
|
||
}
|
||
|
||
// Check for sender (separated by ___)
|
||
let sender: string | undefined;
|
||
let mainPart = workingId;
|
||
if (workingId.includes('___')) {
|
||
const [before, after] = workingId.split('___');
|
||
mainPart = before;
|
||
// Restore colons in sender if any
|
||
sender = after?.replace(/__/g, ':');
|
||
}
|
||
|
||
const [endpoint, ...modelParts] = mainPart.split('__');
|
||
if (!endpoint || modelParts.length === 0) {
|
||
return undefined;
|
||
}
|
||
// Restore colons in model name (model names can contain colons like claude-3:opus)
|
||
const model = modelParts.join(':');
|
||
return { endpoint, model, sender, index };
|
||
}
|
||
|
||
/**
|
||
* Checks if an agent ID represents an ephemeral (non-saved) agent.
|
||
* Real agent IDs always start with "agent_", so anything else is ephemeral.
|
||
*/
|
||
export function isEphemeralAgentId(agentId: string | null | undefined): boolean {
|
||
return !agentId?.startsWith('agent_');
|
||
}
|
||
|
||
/**
|
||
* Strips the index suffix (____N) from an agent ID if present.
|
||
* Works with both ephemeral and real agent IDs.
|
||
*
|
||
* @example
|
||
* stripAgentIdSuffix('agent_abc123____1') // => 'agent_abc123'
|
||
* stripAgentIdSuffix('openAI__gpt-4o___GPT-4o____1') // => 'openAI__gpt-4o___GPT-4o'
|
||
* stripAgentIdSuffix('agent_abc123') // => 'agent_abc123' (unchanged)
|
||
*/
|
||
export function stripAgentIdSuffix(agentId: string): string {
|
||
return agentId.replace(/____\d+$/, '');
|
||
}
|
||
|
||
/**
|
||
* Appends an index suffix (____N) to an agent ID.
|
||
* Used to distinguish parallel agents with the same base ID.
|
||
*
|
||
* @example
|
||
* appendAgentIdSuffix('agent_abc123', 1) // => 'agent_abc123____1'
|
||
* appendAgentIdSuffix('openAI__gpt-4o___GPT-4o', 1) // => 'openAI__gpt-4o___GPT-4o____1'
|
||
*/
|
||
export function appendAgentIdSuffix(agentId: string, index: number): string {
|
||
return `${agentId}____${index}`;
|
||
}
|