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* 📎 feat: Direct Provider Attachment Support for Multimodal Content * 📑 feat: Anthropic Direct Provider Upload (#9072) * feat: implement Anthropic native PDF support with document preservation - Add comprehensive debug logging throughout PDF processing pipeline - Refactor attachment processing to separate image and document handling - Create distinct addImageURLs(), addDocuments(), and processAttachments() methods - Fix critical bugs in stream handling and parameter passing - Add streamToBuffer utility for proper stream-to-buffer conversion - Remove api/agents submodule from repository 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> * chore: remove out of scope formatting changes * fix: stop duplication of file in chat on end of response stream * chore: bring back file search and ocr options * chore: localize upload to provider string in file menu * refactor: change createMenuItems args to fit new pattern introduced by anthropic-native-pdf-support * feat: add cache point for pdfs processed by anthropic endpoint since they are unlikely to change and should benefit from caching * feat: combine Upload Image into Upload to Provider since they both perform direct upload and change provider upload icon to reflect multimodal upload * feat: add citations support according to docs * refactor: remove redundant 'document' check since documents are handled properly by formatMessage in the agents repo now * refactor: change upload logic so anthropic endpoint isn't exempted from normal upload path using Agents for consistency with the rest of the upload logic * fix: include width and height in return from uploadLocalFile so images are correctly identified when going through an AgentUpload in addImageURLs * chore: remove client specific handling since the direct provider stuff is handled by the agent client * feat: handle documents in AgentClient so no need for change to agents repo * chore: removed unused changes * chore: remove auto generated comments from OG commit * feat: add logic for agents to use direct to provider uploads if supported (currently just anthropic) * fix: reintroduce role check to fix render error because of undefined value for Content Part * fix: actually fix render bug by using proper isCreatedByUser check and making sure our mutation of formattedMessage.content is consistent --------- Co-authored-by: Andres Restrepo <andres@thelinuxkid.com> Co-authored-by: Claude <noreply@anthropic.com> 📁 feat: Send Attachments Directly to Provider (OpenAI) (#9098) * refactor: change references from direct upload to direct attach to better reflect functionality since we are just using base64 encoding strategy now rather than Files/File API for sending our attachments directly to the provider, the upload nomenclature no longer makes sense. direct_attach better describes the different methods of sending attachments to providers anyways even if we later introduce direct upload support * feat: add upload to provider option for openai (and agent) ui * chore: move anthropic pdf validator over to packages/api * feat: simple pdf validation according to openai docs * feat: add provider agnostic validatePdf logic to start handling multiple endpoints * feat: add handling for openai specific documentPart formatting * refactor: move require statement to proper place at top of file * chore: add in openAI endpoint for the rest of the document handling logic * feat: add direct attach support for azureOpenAI endpoint and agents * feat: add pdf validation for azureOpenAI endpoint * refactor: unify all the endpoint checks with isDocumentSupportedEndpoint * refactor: consolidate Upload to Provider vs Upload image logic for clarity * refactor: remove anthropic from anthropic_multimodal fileType since we support multiple providers now 🗂️ feat: Send Attachments Directly to Provider (Google) (#9100) * feat: add validation for google PDFs and add google endpoint as a document supporting endpoint * feat: add proper pdf formatting for google endpoints (requires PR #14 in agents) * feat: add multimodal support for google endpoint attachments * feat: add audio file svg * fix: refactor attachments logic so multi-attachment messages work properly * feat: add video file svg * fix: allows for followup questions of uploaded multimodal attachments * fix: remove incorrect final message filtering that was breaking Attachment component rendering fix: manualy rename 'documents' to 'Documents' in git since it wasn't picked up due to case insensitivity in dir name fix: add logic so filepicker for a google agent has proper filetype filtering 🛫 refactor: Move Encoding Logic to packages/api (#9182) * refactor: move audio encode over to TS * refactor: audio encoding now functional in LC again * refactor: move video encode over to TS * refactor: move document encode over to TS * refactor: video encoding now functional in LC again * refactor: document encoding now functional in LC again * fix: extend file type options in AttachFileMenu to include 'google_multimodal' and update dependency array to include agent?.provider * feat: only accept pdfs if responses api is enabled for openai convos chore: address ESLint comments chore: add missing audio mimetype * fix: type safety for message content parts and improve null handling * chore: reorder AttachFileMenuProps for consistency and clarity * chore: import order in AttachFileMenu * fix: improve null handling for text parts in parseTextParts function * fix: remove no longer used unsupported capability error message for file uploads * fix: OpenAI Direct File Attachment Format * fix: update encodeAndFormatDocuments to support OpenAI responses API and enhance document result types * refactor: broaden providers supported for documents * feat: enhance DragDrop context and modal to support document uploads based on provider capabilities * fix: reorder import statements for consistency in video encoding module --------- Co-authored-by: Dustin Healy <54083382+dustinhealy@users.noreply.github.com>
436 lines
12 KiB
TypeScript
436 lines
12 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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gptPluginsSchema,
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// agentsSchema,
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compactAgentsSchema,
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compactGoogleSchema,
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compactPluginsSchema,
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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 gptPluginsSchema
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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 = Exclude<EModelEndpoint, EModelEndpoint.chatGPTBrowser>;
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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.gptPlugins]: gptPluginsSchema,
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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.chatGPTBrowser,
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EModelEndpoint.gptPlugins,
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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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secondaryModels?: 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, secondaryModels } = 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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if (secondaryModels && convo?.agentOptions) {
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convo.agentOptions.model = getFirstDefinedValue(secondaryModels) ?? convo.agentOptions.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: 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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[
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EModelEndpoint.openAI,
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EModelEndpoint.bedrock,
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EModelEndpoint.gptPlugins,
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EModelEndpoint.azureOpenAI,
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EModelEndpoint.chatGPTBrowser,
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].includes(endpoint)
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) {
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if (chatGptLabel) {
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return chatGptLabel;
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} else if (modelLabel) {
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return modelLabel;
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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) ?? 'ChatGPT';
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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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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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| typeof compactPluginsSchema;
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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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[EModelEndpoint.gptPlugins]: compactPluginsSchema,
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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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}) => {
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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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const convo = schema.parse(conversation) as s.TConversation | null;
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// const { models, secondaryModels } = possibleValues ?? {};
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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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// if (secondaryModels && convo.agentOptions) {
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// convo.agentOptionmodel = getFirstDefinedValue(secondaryModels) ?? convo.agentOptionmodel;
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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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