feat: default locale Russian, geo determines language for other countries
- localization-svc: defaultLocale ru, resolveLocale only by geo - web-svc: DEFAULT_LOCALE ru, layout lang=ru, embeddedTranslations fallback ru - countryToLocale: default ru when no country or unknown country Co-authored-by: Cursor <cursoragent@cursor.com>
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102
services/chat-svc/src/lib/agents/search/api.ts
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102
services/chat-svc/src/lib/agents/search/api.ts
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@@ -0,0 +1,102 @@
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import { ResearcherOutput, SearchAgentInput } from './types.js';
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import SessionManager from '../../session.js';
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import { classify } from './classifier.js';
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import Researcher from './researcher/index.js';
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import { getWriterPrompt } from '../../prompts/search/writer.js';
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import { WidgetExecutor } from './widgets/index.js';
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class APISearchAgent {
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async searchAsync(session: SessionManager, input: SearchAgentInput) {
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const classification = await classify({
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chatHistory: input.chatHistory,
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enabledSources: input.config.sources,
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query: input.followUp,
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llm: input.config.llm,
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locale: input.config.locale,
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});
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const widgetPromise = WidgetExecutor.executeAll({
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classification,
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chatHistory: input.chatHistory,
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followUp: input.followUp,
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llm: input.config.llm,
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});
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let searchPromise: Promise<ResearcherOutput> | null = null;
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if (!classification.classification.skipSearch) {
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const researcher = new Researcher();
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searchPromise = researcher.research(SessionManager.createSession(), {
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chatHistory: input.chatHistory,
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followUp: input.followUp,
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classification: classification,
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config: input.config,
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});
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}
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const [widgetOutputs, searchResults] = await Promise.all([
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widgetPromise,
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searchPromise,
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]);
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if (searchResults) {
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session.emit('data', {
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type: 'searchResults',
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data: searchResults.searchFindings,
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});
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}
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session.emit('data', {
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type: 'researchComplete',
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});
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const finalContext =
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searchResults?.searchFindings
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.map(
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(f, index) =>
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`<result index=${index + 1} title=${f.metadata.title}>${f.content}</result>`,
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)
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.join('\n') || '';
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const widgetContext = widgetOutputs
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.map((o) => {
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return `<result>${o.llmContext}</result>`;
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})
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.join('\n-------------\n');
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const finalContextWithWidgets = `<search_results note="These are the search results and assistant can cite these">\n${finalContext}\n</search_results>\n<widgets_result noteForAssistant="Its output is already showed to the user, assistant can use this information to answer the query but do not CITE this as a souce">\n${widgetContext}\n</widgets_result>`;
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const writerPrompt = getWriterPrompt(
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finalContextWithWidgets,
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input.config.systemInstructions,
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input.config.mode,
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input.config.locale,
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input.config.memoryContext,
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);
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const answerStream = input.config.llm.streamText({
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messages: [
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{
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role: 'system',
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content: writerPrompt,
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},
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...input.chatHistory,
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{
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role: 'user',
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content: input.followUp,
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},
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],
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});
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for await (const chunk of answerStream) {
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session.emit('data', {
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type: 'response',
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data: chunk.contentChunk,
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});
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}
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session.emit('end', {});
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}
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}
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export default APISearchAgent;
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53
services/chat-svc/src/lib/agents/search/classifier.ts
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53
services/chat-svc/src/lib/agents/search/classifier.ts
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@@ -0,0 +1,53 @@
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import z from 'zod';
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import { ClassifierInput } from './types.js';
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import { getClassifierPrompt } from '../../prompts/search/classifier.js';
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import formatChatHistoryAsString from '../../utils/formatHistory.js';
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const schema = z.object({
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classification: z.object({
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skipSearch: z
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.boolean()
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.describe('Indicates whether to skip the search step.'),
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personalSearch: z
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.boolean()
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.describe('Indicates whether to perform a personal search.'),
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academicSearch: z
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.boolean()
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.describe('Indicates whether to perform an academic search.'),
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discussionSearch: z
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.boolean()
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.describe('Indicates whether to perform a discussion search.'),
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showWeatherWidget: z
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.boolean()
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.describe('Indicates whether to show the weather widget.'),
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showStockWidget: z
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.boolean()
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.describe('Indicates whether to show the stock widget.'),
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showCalculationWidget: z
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.boolean()
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.describe('Indicates whether to show the calculation widget.'),
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}),
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standaloneFollowUp: z
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.string()
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.describe(
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"A self-contained, context-independent reformulation of the user's question.",
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),
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});
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export const classify = async (input: ClassifierInput) => {
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const output = await input.llm.generateObject<typeof schema>({
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messages: [
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{
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role: 'system',
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content: getClassifierPrompt(input.locale),
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},
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{
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role: 'user',
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content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_query>\n${input.query}\n</user_query>`,
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},
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],
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schema,
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});
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return output;
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};
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309
services/chat-svc/src/lib/agents/search/index.ts
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309
services/chat-svc/src/lib/agents/search/index.ts
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@@ -0,0 +1,309 @@
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import type BaseLLM from '../../models/base/llm.js';
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import { ResearcherOutput, SearchAgentInput } from './types.js';
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import SessionManager from '../../session.js';
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import { classify } from './classifier.js';
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import Researcher from './researcher/index.js';
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import { getWriterPrompt, getSynthesisPrompt } from '../../prompts/search/writer.js';
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import { WidgetExecutor } from './widgets/index.js';
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import { TextBlock } from '../../types.js';
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class SearchAgent {
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async searchAsync(session: SessionManager, input: SearchAgentInput) {
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try {
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await this.doSearch(session, input);
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} catch (err) {
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console.error('[SearchAgent] Fatal:', err);
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const blocks = session.getAllBlocks();
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const sourceBlock = blocks.find((b) => b.type === 'source');
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let sources: { metadata?: { title?: string } }[] =
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sourceBlock?.type === 'source' ? sourceBlock.data : [];
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if (sources.length === 0) {
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const researchBlock = blocks.find(
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(b): b is typeof b & { data: { subSteps?: { type: string; reading?: { metadata?: { title?: string } }[] }[] } } =>
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b.type === 'research' && 'subSteps' in (b.data ?? {}),
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);
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const searchStep = researchBlock?.data?.subSteps?.find(
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(s) => s.type === 'search_results' && Array.isArray(s.reading),
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);
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if (searchStep && 'reading' in searchStep) {
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sources = searchStep.reading ?? [];
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}
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}
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if (sources.length > 0) {
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const lines = sources.slice(0, 10).map(
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(s: { metadata?: { title?: string } }, i: number) =>
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`${i + 1}. **${s?.metadata?.title ?? 'Источник'}**`,
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);
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session.emitBlock({
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id: crypto.randomUUID(),
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type: 'text',
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data: `## По найденным источникам\n\n${lines.join('\n')}\n\n*Ответ LLM недоступен (400). Проверьте модель gemini-3-flash в Settings или попробуйте другую модель.*`,
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});
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} else {
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session.emitBlock({
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id: crypto.randomUUID(),
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type: 'text',
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data: `Ошибка: ${err instanceof Error ? err.message : String(err)}. Проверьте LLM в Settings.`,
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});
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}
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session.emit('end', {});
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}
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}
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private async doSearch(session: SessionManager, input: SearchAgentInput) {
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const lib = input.config.libraryClient;
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if (lib?.enabled) {
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await lib.upsertMessage(input.chatId, input.messageId, input.followUp, {
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backendId: session.id,
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responseBlocks: [],
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status: 'answering',
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sources: (input.config.sources as string[]) ?? [],
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});
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}
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const classification = await classify({
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chatHistory: input.chatHistory,
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enabledSources: input.config.sources,
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query: input.followUp,
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llm: input.config.llm,
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locale: input.config.locale,
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});
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const widgetPromise = WidgetExecutor.executeAll({
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classification,
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chatHistory: input.chatHistory,
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followUp: input.followUp,
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llm: input.config.llm,
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}).then((widgetOutputs) => {
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widgetOutputs.forEach((o) => {
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session.emitBlock({
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id: crypto.randomUUID(),
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type: 'widget',
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data: {
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widgetType: o.type,
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params: o.data,
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},
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});
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});
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return widgetOutputs;
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});
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let searchPromise: Promise<ResearcherOutput> | null = null;
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if (!classification.classification.skipSearch) {
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const researcher = new Researcher();
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searchPromise = researcher.research(session, {
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chatHistory: input.chatHistory,
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followUp: input.followUp,
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classification: classification,
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config: input.config,
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});
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}
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const [widgetOutputs, searchResults] = await Promise.all([
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widgetPromise,
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searchPromise,
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]);
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session.emit('data', {
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type: 'researchComplete',
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});
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const MAX_RESULTS_FOR_WRITER = 15;
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const MAX_CONTENT_PER_RESULT = 180;
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const findingsForWriter =
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searchResults?.searchFindings.slice(0, MAX_RESULTS_FOR_WRITER) ?? [];
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const finalContext =
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findingsForWriter
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.map((f, index) => {
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const content =
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f.content.length > MAX_CONTENT_PER_RESULT
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? f.content.slice(0, MAX_CONTENT_PER_RESULT) + '…'
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: f.content;
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return `<result index=${index + 1} title="${String(f.metadata.title).replace(/"/g, "'")}">${content}</result>`;
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})
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.join('\n') || '';
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const widgetContext = widgetOutputs
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.map((o) => {
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return `<result>${o.llmContext}</result>`;
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})
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.join('\n-------------\n');
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const finalContextWithWidgets = `<search_results note="These are the search results and assistant can cite these">\n${finalContext}\n</search_results>\n<widgets_result noteForAssistant="Its output is already showed to the user, assistant can use this information to answer the query but do not CITE this as a souce">\n${widgetContext}\n</widgets_result>`;
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const writerPrompt = getWriterPrompt(
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finalContextWithWidgets,
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input.config.systemInstructions,
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input.config.mode,
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input.config.locale,
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input.config.memoryContext,
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input.config.answerMode,
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input.config.responsePrefs,
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input.config.learningMode,
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);
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const councilLlms = input.config.councilLlms;
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if (councilLlms && councilLlms.length === 3) {
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await this.runCouncilWritersAndSynthesis(
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session,
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input,
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writerPrompt,
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findingsForWriter,
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councilLlms,
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);
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return;
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}
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const answerStream = input.config.llm.streamText({
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messages: [
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{ role: 'system', content: writerPrompt },
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...input.chatHistory,
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{ role: 'user', content: input.followUp },
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],
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options: { maxTokens: 4096 },
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});
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let responseBlockId = '';
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let hasContent = false;
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for await (const chunk of answerStream) {
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if (!chunk.contentChunk && !responseBlockId) continue;
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if (!responseBlockId) {
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const block: TextBlock = {
|
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id: crypto.randomUUID(),
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type: 'text',
|
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data: chunk.contentChunk,
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};
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session.emitBlock(block);
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responseBlockId = block.id;
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if (chunk.contentChunk) hasContent = true;
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} else {
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const block = session.getBlock(responseBlockId) as TextBlock | null;
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if (block) {
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block.data += chunk.contentChunk;
|
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if (chunk.contentChunk) hasContent = true;
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session.updateBlock(block.id, [
|
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{ op: 'replace', path: '/data', value: block.data },
|
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]);
|
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}
|
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}
|
||||
}
|
||||
|
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if (!hasContent && findingsForWriter.length > 0) {
|
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const lines = findingsForWriter.slice(0, 10).map((f, i) => {
|
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const title = f.metadata.title ?? 'Без названия';
|
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const excerpt =
|
||||
f.content.length > 120 ? f.content.slice(0, 120) + '…' : f.content;
|
||||
return `${i + 1}. **${title}** — ${excerpt}`;
|
||||
});
|
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session.emitBlock({
|
||||
id: crypto.randomUUID(),
|
||||
type: 'text',
|
||||
data: `## По найденным источникам\n\n${lines.join('\n\n')}\n\n*Ответ LLM недоступен. Проверьте модель в Settings.*`,
|
||||
});
|
||||
}
|
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|
||||
session.emit('end', {});
|
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await this.persistMessage(session, input.chatId, input.messageId, input.config.libraryClient);
|
||||
}
|
||||
|
||||
/** Model Council: run 3 writers in parallel, synthesize, stream synthesis */
|
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private async runCouncilWritersAndSynthesis(
|
||||
session: SessionManager,
|
||||
input: SearchAgentInput,
|
||||
writerPrompt: string,
|
||||
findingsForWriter: { content: string; metadata: { title?: string } }[],
|
||||
councilLlms: [BaseLLM<any>, BaseLLM<any>, BaseLLM<any>],
|
||||
) {
|
||||
const messages = [
|
||||
{ role: 'system' as const, content: writerPrompt },
|
||||
...input.chatHistory,
|
||||
{ role: 'user' as const, content: input.followUp },
|
||||
];
|
||||
const writerInput = { messages, options: { maxTokens: 4096 } };
|
||||
|
||||
const [r1, r2, r3] = await Promise.all([
|
||||
councilLlms[0].generateText(writerInput),
|
||||
councilLlms[1].generateText(writerInput),
|
||||
councilLlms[2].generateText(writerInput),
|
||||
]);
|
||||
|
||||
const answer1 = r1.content ?? '';
|
||||
const answer2 = r2.content ?? '';
|
||||
const answer3 = r3.content ?? '';
|
||||
|
||||
const synthesisPrompt = getSynthesisPrompt(
|
||||
input.followUp,
|
||||
answer1,
|
||||
answer2,
|
||||
answer3,
|
||||
input.config.locale,
|
||||
);
|
||||
const synthesisStream = councilLlms[0].streamText({
|
||||
messages: [{ role: 'user' as const, content: synthesisPrompt }],
|
||||
options: { maxTokens: 4096 },
|
||||
});
|
||||
|
||||
let responseBlockId = '';
|
||||
let hasContent = false;
|
||||
|
||||
for await (const chunk of synthesisStream) {
|
||||
if (!chunk.contentChunk && !responseBlockId) continue;
|
||||
if (!responseBlockId) {
|
||||
const block: TextBlock = {
|
||||
id: crypto.randomUUID(),
|
||||
type: 'text',
|
||||
data: chunk.contentChunk ?? '',
|
||||
};
|
||||
session.emitBlock(block);
|
||||
responseBlockId = block.id;
|
||||
if (chunk.contentChunk) hasContent = true;
|
||||
} else {
|
||||
const block = session.getBlock(responseBlockId) as TextBlock | null;
|
||||
if (block) {
|
||||
block.data += chunk.contentChunk ?? '';
|
||||
if (chunk.contentChunk) hasContent = true;
|
||||
session.updateBlock(block.id, [
|
||||
{ op: 'replace', path: '/data', value: block.data },
|
||||
]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (!hasContent && findingsForWriter.length > 0) {
|
||||
const lines = findingsForWriter.slice(0, 10).map((f, i) => {
|
||||
const title = f.metadata.title ?? 'Без названия';
|
||||
const excerpt = f.content.length > 120 ? f.content.slice(0, 120) + '…' : f.content;
|
||||
return `${i + 1}. **${title}** — ${excerpt}`;
|
||||
});
|
||||
session.emitBlock({
|
||||
id: crypto.randomUUID(),
|
||||
type: 'text',
|
||||
data: `## По найденным источникам\n\n${lines.join('\n\n')}\n\n*Model Council: синтез недоступен. Проверьте модели в Settings.*`,
|
||||
});
|
||||
}
|
||||
|
||||
session.emit('end', {});
|
||||
await this.persistMessage(session, input.chatId, input.messageId, input.config.libraryClient);
|
||||
}
|
||||
|
||||
private async persistMessage(
|
||||
session: SessionManager,
|
||||
chatId: string,
|
||||
messageId: string,
|
||||
libraryClient?: SearchAgentInput['config']['libraryClient'],
|
||||
) {
|
||||
if (!libraryClient?.enabled) return;
|
||||
try {
|
||||
await libraryClient.updateMessage(chatId, messageId, {
|
||||
status: 'completed',
|
||||
responseBlocks: session.getAllBlocks(),
|
||||
});
|
||||
} catch (err) {
|
||||
console.error('[SearchAgent] LibraryClient update failed:', err);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export default SearchAgent;
|
||||
@@ -0,0 +1,129 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
import { Chunk, SearchResultsResearchBlock } from '../../../../types.js';
|
||||
import { searchSearxng } from '../../../../searxng.js';
|
||||
|
||||
const schema = z.object({
|
||||
queries: z.array(z.string()).describe('List of academic search queries'),
|
||||
});
|
||||
|
||||
const academicSearchDescription = `
|
||||
Use this tool to perform academic searches for scholarly articles, papers, and research studies relevant to the user's query. Provide a list of concise search queries that will help gather comprehensive academic information on the topic at hand.
|
||||
You can provide up to 3 queries at a time. Make sure the queries are specific and relevant to the user's needs.
|
||||
|
||||
For example, if the user is interested in recent advancements in renewable energy, your queries could be:
|
||||
1. "Recent advancements in renewable energy 2024"
|
||||
2. "Cutting-edge research on solar power technologies"
|
||||
3. "Innovations in wind energy systems"
|
||||
|
||||
If this tool is present and no other tools are more relevant, you MUST use this tool to get the needed academic information.
|
||||
`;
|
||||
|
||||
const academicSearchAction: ResearchAction<typeof schema> = {
|
||||
name: 'academic_search',
|
||||
schema: schema,
|
||||
getDescription: () => academicSearchDescription,
|
||||
getToolDescription: () =>
|
||||
"Use this tool to perform academic searches for scholarly articles, papers, and research studies relevant to the user's query. Provide a list of concise search queries that will help gather comprehensive academic information on the topic at hand.",
|
||||
enabled: (config) =>
|
||||
config.sources.includes('academic') &&
|
||||
config.classification.classification.skipSearch === false &&
|
||||
config.classification.classification.academicSearch === true,
|
||||
execute: async (input, additionalConfig) => {
|
||||
input.queries = input.queries.slice(0, 3);
|
||||
|
||||
const researchBlock = additionalConfig.session.getBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
);
|
||||
|
||||
if (researchBlock && researchBlock.type === 'research') {
|
||||
researchBlock.data.subSteps.push({
|
||||
type: 'searching',
|
||||
id: crypto.randomUUID(),
|
||||
searching: input.queries,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
|
||||
const searchResultsBlockId = crypto.randomUUID();
|
||||
let searchResultsEmitted = false;
|
||||
|
||||
let results: Chunk[] = [];
|
||||
|
||||
const search = async (q: string) => {
|
||||
const res = await searchSearxng(q, {
|
||||
engines: ['arxiv', 'google scholar', 'pubmed'],
|
||||
});
|
||||
|
||||
const resultChunks: Chunk[] = res.results.map((r) => ({
|
||||
content: r.content || r.title,
|
||||
metadata: {
|
||||
title: r.title,
|
||||
url: r.url,
|
||||
},
|
||||
}));
|
||||
|
||||
results.push(...resultChunks);
|
||||
|
||||
if (
|
||||
!searchResultsEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
searchResultsEmitted = true;
|
||||
|
||||
researchBlock.data.subSteps.push({
|
||||
id: searchResultsBlockId,
|
||||
type: 'search_results',
|
||||
reading: resultChunks,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
} else if (
|
||||
searchResultsEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
const subStepIndex = researchBlock.data.subSteps.findIndex(
|
||||
(step) => step.id === searchResultsBlockId,
|
||||
);
|
||||
|
||||
const subStep = researchBlock.data.subSteps[
|
||||
subStepIndex
|
||||
] as SearchResultsResearchBlock;
|
||||
|
||||
subStep.reading.push(...resultChunks);
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
};
|
||||
|
||||
await Promise.all(input.queries.map(search));
|
||||
|
||||
return {
|
||||
type: 'search_results',
|
||||
results,
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default academicSearchAction;
|
||||
@@ -0,0 +1,24 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
|
||||
const actionDescription = `
|
||||
Use this action ONLY when you have completed all necessary research and are ready to provide a final answer to the user. This indicates that you have gathered sufficient information from previous steps and are concluding the research process.
|
||||
YOU MUST CALL THIS ACTION TO SIGNAL COMPLETION; DO NOT OUTPUT FINAL ANSWERS DIRECTLY TO THE USER.
|
||||
IT WILL BE AUTOMATICALLY TRIGGERED IF MAXIMUM ITERATIONS ARE REACHED SO IF YOU'RE LOW ON ITERATIONS, DON'T CALL IT AND INSTEAD FOCUS ON GATHERING ESSENTIAL INFO FIRST.
|
||||
`;
|
||||
|
||||
const doneAction: ResearchAction<any> = {
|
||||
name: 'done',
|
||||
schema: z.object({}),
|
||||
getToolDescription: () =>
|
||||
'Only call this after __reasoning_preamble AND after any other needed tool calls when you truly have enough to answer. Do not call if information is still missing.',
|
||||
getDescription: () => actionDescription,
|
||||
enabled: (_) => true,
|
||||
execute: async (params, additionalConfig) => {
|
||||
return {
|
||||
type: 'done',
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default doneAction;
|
||||
@@ -0,0 +1,18 @@
|
||||
import academicSearchAction from './academicSearch.js';
|
||||
import doneAction from './done.js';
|
||||
import planAction from './plan.js';
|
||||
import ActionRegistry from './registry.js';
|
||||
import scrapeURLAction from './scrapeURL.js';
|
||||
import socialSearchAction from './socialSearch.js';
|
||||
import uploadsSearchAction from './uploadsSearch.js';
|
||||
import webSearchAction from './webSearch.js';
|
||||
|
||||
ActionRegistry.register(webSearchAction);
|
||||
ActionRegistry.register(doneAction);
|
||||
ActionRegistry.register(planAction);
|
||||
ActionRegistry.register(scrapeURLAction);
|
||||
ActionRegistry.register(uploadsSearchAction);
|
||||
ActionRegistry.register(academicSearchAction);
|
||||
ActionRegistry.register(socialSearchAction);
|
||||
|
||||
export { ActionRegistry };
|
||||
@@ -0,0 +1,40 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
|
||||
const schema = z.object({
|
||||
plan: z
|
||||
.string()
|
||||
.describe(
|
||||
'A concise natural-language plan in one short paragraph. Open with a short intent phrase (e.g., "Okay, the user wants to...", "Searching for...", "Looking into...") and lay out the steps you will take.',
|
||||
),
|
||||
});
|
||||
|
||||
const actionDescription = `
|
||||
Use this tool FIRST on every turn to state your plan in natural language before any other action. Keep it short, action-focused, and tailored to the current query.
|
||||
Make sure to not include reference to any tools or actions you might take, just the plan itself. The user isn't aware about tools, but they love to see your thought process.
|
||||
|
||||
Here are some examples of good plans:
|
||||
<examples>
|
||||
- "Okay, the user wants to know the latest advancements in renewable energy. I will start by looking for recent articles and studies on this topic, then summarize the key points." -> "I have gathered enough information to provide a comprehensive answer."
|
||||
- "The user is asking about the health benefits of a Mediterranean diet. I will search for scientific studies and expert opinions on this diet, then compile the findings into a clear summary." -> "I have gathered information about the Mediterranean diet and its health benefits, I will now look up for any recent studies to ensure the information is current."
|
||||
</examples>
|
||||
|
||||
YOU CAN NEVER CALL ANY OTHER TOOL BEFORE CALLING THIS ONE FIRST, IF YOU DO, THAT CALL WOULD BE IGNORED.
|
||||
`;
|
||||
|
||||
const planAction: ResearchAction<typeof schema> = {
|
||||
name: '__reasoning_preamble',
|
||||
schema: schema,
|
||||
getToolDescription: () =>
|
||||
'Use this FIRST on every turn to state your plan in natural language before any other action. Keep it short, action-focused, and tailored to the current query.',
|
||||
getDescription: () => actionDescription,
|
||||
enabled: (config) => config.mode !== 'speed',
|
||||
execute: async (input, _) => {
|
||||
return {
|
||||
type: 'reasoning',
|
||||
reasoning: input.plan,
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default planAction;
|
||||
@@ -0,0 +1,108 @@
|
||||
import { Tool, ToolCall } from '../../../../models/types.js';
|
||||
import {
|
||||
ActionOutput,
|
||||
AdditionalConfig,
|
||||
ClassifierOutput,
|
||||
ResearchAction,
|
||||
SearchAgentConfig,
|
||||
SearchSources,
|
||||
} from '../../types.js';
|
||||
|
||||
class ActionRegistry {
|
||||
private static actions: Map<string, ResearchAction> = new Map();
|
||||
|
||||
static register(action: ResearchAction<any>) {
|
||||
this.actions.set(action.name, action);
|
||||
}
|
||||
|
||||
static get(name: string): ResearchAction | undefined {
|
||||
return this.actions.get(name);
|
||||
}
|
||||
|
||||
static getAvailableActions(config: {
|
||||
classification: ClassifierOutput;
|
||||
fileIds: string[];
|
||||
mode: SearchAgentConfig['mode'];
|
||||
sources: SearchSources[];
|
||||
hasEmbedding?: boolean;
|
||||
}): ResearchAction[] {
|
||||
return Array.from(this.actions.values()).filter((action) =>
|
||||
action.enabled(config),
|
||||
);
|
||||
}
|
||||
|
||||
static getAvailableActionTools(config: {
|
||||
classification: ClassifierOutput;
|
||||
fileIds: string[];
|
||||
mode: SearchAgentConfig['mode'];
|
||||
sources: SearchSources[];
|
||||
hasEmbedding?: boolean;
|
||||
}): Tool[] {
|
||||
const availableActions = this.getAvailableActions(config);
|
||||
|
||||
return availableActions.map((action) => ({
|
||||
name: action.name,
|
||||
description: action.getToolDescription({ mode: config.mode }),
|
||||
schema: action.schema,
|
||||
}));
|
||||
}
|
||||
|
||||
static getAvailableActionsDescriptions(config: {
|
||||
classification: ClassifierOutput;
|
||||
fileIds: string[];
|
||||
mode: SearchAgentConfig['mode'];
|
||||
sources: SearchSources[];
|
||||
hasEmbedding?: boolean;
|
||||
}): string {
|
||||
const availableActions = this.getAvailableActions(config);
|
||||
|
||||
return availableActions
|
||||
.map(
|
||||
(action) =>
|
||||
`<tool name="${action.name}">\n${action.getDescription({ mode: config.mode })}\n</tool>`,
|
||||
)
|
||||
.join('\n\n');
|
||||
}
|
||||
|
||||
static async execute(
|
||||
name: string,
|
||||
params: any,
|
||||
additionalConfig: AdditionalConfig & {
|
||||
researchBlockId: string;
|
||||
fileIds: string[];
|
||||
},
|
||||
) {
|
||||
const action = this.actions.get(name);
|
||||
|
||||
if (!action) {
|
||||
throw new Error(`Action with name ${name} not found`);
|
||||
}
|
||||
|
||||
return action.execute(params, additionalConfig);
|
||||
}
|
||||
|
||||
static async executeAll(
|
||||
actions: ToolCall[],
|
||||
additionalConfig: AdditionalConfig & {
|
||||
researchBlockId: string;
|
||||
fileIds: string[];
|
||||
},
|
||||
): Promise<ActionOutput[]> {
|
||||
const results: ActionOutput[] = [];
|
||||
|
||||
await Promise.all(
|
||||
actions.map(async (actionConfig) => {
|
||||
const output = await this.execute(
|
||||
actionConfig.name,
|
||||
actionConfig.arguments,
|
||||
additionalConfig,
|
||||
);
|
||||
results.push(output);
|
||||
}),
|
||||
);
|
||||
|
||||
return results;
|
||||
}
|
||||
}
|
||||
|
||||
export default ActionRegistry;
|
||||
@@ -0,0 +1,139 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
import { Chunk, ReadingResearchBlock } from '../../../../types.js';
|
||||
import TurnDown from 'turndown';
|
||||
import path from 'path';
|
||||
|
||||
const turndownService = new TurnDown();
|
||||
|
||||
const schema = z.object({
|
||||
urls: z.array(z.string()).describe('A list of URLs to scrape content from.'),
|
||||
});
|
||||
|
||||
const actionDescription = `
|
||||
Use this tool to scrape and extract content from the provided URLs. This is useful when you the user has asked you to extract or summarize information from specific web pages. You can provide up to 3 URLs at a time. NEVER CALL THIS TOOL EXPLICITLY YOURSELF UNLESS INSTRUCTED TO DO SO BY THE USER.
|
||||
You should only call this tool when the user has specifically requested information from certain web pages, never call this yourself to get extra information without user instruction.
|
||||
|
||||
For example, if the user says "Please summarize the content of https://example.com/article", you can call this tool with that URL to get the content and then provide the summary or "What does X mean according to https://example.com/page", you can call this tool with that URL to get the content and provide the explanation.
|
||||
`;
|
||||
|
||||
const scrapeURLAction: ResearchAction<typeof schema> = {
|
||||
name: 'scrape_url',
|
||||
schema: schema,
|
||||
getToolDescription: () =>
|
||||
'Use this tool to scrape and extract content from the provided URLs. This is useful when you the user has asked you to extract or summarize information from specific web pages. You can provide up to 3 URLs at a time. NEVER CALL THIS TOOL EXPLICITLY YOURSELF UNLESS INSTRUCTED TO DO SO BY THE USER.',
|
||||
getDescription: () => actionDescription,
|
||||
enabled: (_) => true,
|
||||
execute: async (params, additionalConfig) => {
|
||||
params.urls = params.urls.slice(0, 3);
|
||||
|
||||
let readingBlockId = crypto.randomUUID();
|
||||
let readingEmitted = false;
|
||||
|
||||
const researchBlock = additionalConfig.session.getBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
);
|
||||
|
||||
const results: Chunk[] = [];
|
||||
|
||||
await Promise.all(
|
||||
params.urls.map(async (url) => {
|
||||
try {
|
||||
const res = await fetch(url);
|
||||
const text = await res.text();
|
||||
|
||||
const title =
|
||||
text.match(/<title>(.*?)<\/title>/i)?.[1] || `Content from ${url}`;
|
||||
|
||||
if (
|
||||
!readingEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
readingEmitted = true;
|
||||
researchBlock.data.subSteps.push({
|
||||
id: readingBlockId,
|
||||
type: 'reading',
|
||||
reading: [
|
||||
{
|
||||
content: '',
|
||||
metadata: {
|
||||
url,
|
||||
title: title,
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
[
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
],
|
||||
);
|
||||
} else if (
|
||||
readingEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
const subStepIndex = researchBlock.data.subSteps.findIndex(
|
||||
(step: any) => step.id === readingBlockId,
|
||||
);
|
||||
|
||||
const subStep = researchBlock.data.subSteps[
|
||||
subStepIndex
|
||||
] as ReadingResearchBlock;
|
||||
|
||||
subStep.reading.push({
|
||||
content: '',
|
||||
metadata: {
|
||||
url,
|
||||
title: title,
|
||||
},
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
[
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
],
|
||||
);
|
||||
}
|
||||
|
||||
const markdown = turndownService.turndown(text);
|
||||
|
||||
results.push({
|
||||
content: markdown,
|
||||
metadata: {
|
||||
url,
|
||||
title: title,
|
||||
},
|
||||
});
|
||||
} catch (error) {
|
||||
results.push({
|
||||
content: `Failed to fetch content from ${url}: ${error}`,
|
||||
metadata: {
|
||||
url,
|
||||
title: `Error fetching ${url}`,
|
||||
},
|
||||
});
|
||||
}
|
||||
}),
|
||||
);
|
||||
|
||||
return {
|
||||
type: 'search_results',
|
||||
results,
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default scrapeURLAction;
|
||||
@@ -0,0 +1,129 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
import { Chunk, SearchResultsResearchBlock } from '../../../../types.js';
|
||||
import { searchSearxng } from '../../../../searxng.js';
|
||||
|
||||
const schema = z.object({
|
||||
queries: z.array(z.string()).describe('List of social search queries'),
|
||||
});
|
||||
|
||||
const socialSearchDescription = `
|
||||
Use this tool to perform social media searches for relevant posts, discussions, and trends related to the user's query. Provide a list of concise search queries that will help gather comprehensive social media information on the topic at hand.
|
||||
You can provide up to 3 queries at a time. Make sure the queries are specific and relevant to the user's needs.
|
||||
|
||||
For example, if the user is interested in public opinion on electric vehicles, your queries could be:
|
||||
1. "Electric vehicles public opinion 2024"
|
||||
2. "Social media discussions on EV adoption"
|
||||
3. "Trends in electric vehicle usage"
|
||||
|
||||
If this tool is present and no other tools are more relevant, you MUST use this tool to get the needed social media information.
|
||||
`;
|
||||
|
||||
const socialSearchAction: ResearchAction<typeof schema> = {
|
||||
name: 'social_search',
|
||||
schema: schema,
|
||||
getDescription: () => socialSearchDescription,
|
||||
getToolDescription: () =>
|
||||
"Use this tool to perform social media searches for relevant posts, discussions, and trends related to the user's query. Provide a list of concise search queries that will help gather comprehensive social media information on the topic at hand.",
|
||||
enabled: (config) =>
|
||||
config.sources.includes('discussions') &&
|
||||
config.classification.classification.skipSearch === false &&
|
||||
config.classification.classification.discussionSearch === true,
|
||||
execute: async (input, additionalConfig) => {
|
||||
input.queries = input.queries.slice(0, 3);
|
||||
|
||||
const researchBlock = additionalConfig.session.getBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
);
|
||||
|
||||
if (researchBlock && researchBlock.type === 'research') {
|
||||
researchBlock.data.subSteps.push({
|
||||
type: 'searching',
|
||||
id: crypto.randomUUID(),
|
||||
searching: input.queries,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
|
||||
const searchResultsBlockId = crypto.randomUUID();
|
||||
let searchResultsEmitted = false;
|
||||
|
||||
let results: Chunk[] = [];
|
||||
|
||||
const search = async (q: string) => {
|
||||
const res = await searchSearxng(q, {
|
||||
engines: ['reddit'],
|
||||
});
|
||||
|
||||
const resultChunks: Chunk[] = res.results.map((r) => ({
|
||||
content: r.content || r.title,
|
||||
metadata: {
|
||||
title: r.title,
|
||||
url: r.url,
|
||||
},
|
||||
}));
|
||||
|
||||
results.push(...resultChunks);
|
||||
|
||||
if (
|
||||
!searchResultsEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
searchResultsEmitted = true;
|
||||
|
||||
researchBlock.data.subSteps.push({
|
||||
id: searchResultsBlockId,
|
||||
type: 'search_results',
|
||||
reading: resultChunks,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
} else if (
|
||||
searchResultsEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
const subStepIndex = researchBlock.data.subSteps.findIndex(
|
||||
(step) => step.id === searchResultsBlockId,
|
||||
);
|
||||
|
||||
const subStep = researchBlock.data.subSteps[
|
||||
subStepIndex
|
||||
] as SearchResultsResearchBlock;
|
||||
|
||||
subStep.reading.push(...resultChunks);
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
};
|
||||
|
||||
await Promise.all(input.queries.map(search));
|
||||
|
||||
return {
|
||||
type: 'search_results',
|
||||
results,
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default socialSearchAction;
|
||||
@@ -0,0 +1,107 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
import UploadStore from '../../../../uploads/store.js';
|
||||
|
||||
const schema = z.object({
|
||||
queries: z
|
||||
.array(z.string())
|
||||
.describe(
|
||||
'A list of queries to search in user uploaded files. Can be a maximum of 3 queries.',
|
||||
),
|
||||
});
|
||||
|
||||
const uploadsSearchAction: ResearchAction<typeof schema> = {
|
||||
name: 'uploads_search',
|
||||
enabled: (config) =>
|
||||
config.hasEmbedding !== false &&
|
||||
((config.classification.classification.personalSearch &&
|
||||
config.fileIds.length > 0) ||
|
||||
config.fileIds.length > 0),
|
||||
schema,
|
||||
getToolDescription: () =>
|
||||
`Use this tool to perform searches over the user's uploaded files. This is useful when you need to gather information from the user's documents to answer their questions. You can provide up to 3 queries at a time. You will have to use this every single time if this is present and relevant.`,
|
||||
getDescription: () => `
|
||||
Use this tool to perform searches over the user's uploaded files. This is useful when you need to gather information from the user's documents to answer their questions. You can provide up to 3 queries at a time. You will have to use this every single time if this is present and relevant.
|
||||
Always ensure that the queries you use are directly relevant to the user's request and pertain to the content of their uploaded files.
|
||||
|
||||
For example, if the user says "Please find information about X in my uploaded documents", you can call this tool with a query related to X to retrieve the relevant information from their files.
|
||||
Never use this tool to search the web or for information that is not contained within the user's uploaded files.
|
||||
`,
|
||||
execute: async (input, additionalConfig) => {
|
||||
if (!additionalConfig.embedding) {
|
||||
return { type: 'search_results' as const, results: [] };
|
||||
}
|
||||
|
||||
input.queries = input.queries.slice(0, 3);
|
||||
|
||||
const researchBlock = additionalConfig.session.getBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
);
|
||||
|
||||
if (researchBlock && researchBlock.type === 'research') {
|
||||
researchBlock.data.subSteps.push({
|
||||
id: crypto.randomUUID(),
|
||||
type: 'upload_searching',
|
||||
queries: input.queries,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
|
||||
const uploadStore = new UploadStore({
|
||||
embeddingModel: additionalConfig.embedding,
|
||||
fileIds: additionalConfig.fileIds,
|
||||
});
|
||||
|
||||
const results = await uploadStore.query(input.queries, 10);
|
||||
|
||||
const seenIds = new Map<string, number>();
|
||||
|
||||
const filteredSearchResults = results
|
||||
.map((result, index) => {
|
||||
if (result.metadata?.url as string && !seenIds.has(result.metadata?.url as string)) {
|
||||
seenIds.set(result.metadata?.url as string, index);
|
||||
return result;
|
||||
} else if (result.metadata?.url as string && seenIds.has(result.metadata?.url as string)) {
|
||||
const existingIndex = seenIds.get(result.metadata?.url as string)!;
|
||||
const existingResult = results[existingIndex];
|
||||
|
||||
existingResult.content += `\n\n${result.content}`;
|
||||
|
||||
return undefined;
|
||||
}
|
||||
|
||||
return result;
|
||||
})
|
||||
.filter((r) => r !== undefined);
|
||||
|
||||
if (researchBlock && researchBlock.type === 'research') {
|
||||
researchBlock.data.subSteps.push({
|
||||
id: crypto.randomUUID(),
|
||||
type: 'upload_search_results',
|
||||
results: filteredSearchResults,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
|
||||
return {
|
||||
type: 'search_results',
|
||||
results: filteredSearchResults,
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default uploadsSearchAction;
|
||||
@@ -0,0 +1,182 @@
|
||||
import z from 'zod';
|
||||
import { ResearchAction } from '../../types.js';
|
||||
import { searchSearxng } from '../../../../searxng.js';
|
||||
import { Chunk, SearchResultsResearchBlock } from '../../../../types.js';
|
||||
|
||||
const actionSchema = z.object({
|
||||
type: z.literal('web_search'),
|
||||
queries: z
|
||||
.array(z.string())
|
||||
.describe('An array of search queries to perform web searches for.'),
|
||||
});
|
||||
|
||||
const speedModePrompt = `
|
||||
Use this tool to perform web searches based on the provided queries. This is useful when you need to gather information from the web to answer the user's questions. You can provide up to 3 queries at a time. You will have to use this every single time if this is present and relevant.
|
||||
You are currently on speed mode, meaning you would only get to call this tool once. Make sure to prioritize the most important queries that are likely to get you the needed information in one go.
|
||||
|
||||
Your queries should be very targeted and specific to the information you need, avoid broad or generic queries.
|
||||
Your queries shouldn't be sentences but rather keywords that are SEO friendly and can be used to search the web for information.
|
||||
|
||||
For example, if the user is asking about the features of a new technology, you might use queries like "GPT-5.1 features", "GPT-5.1 release date", "GPT-5.1 improvements" rather than a broad query like "Tell me about GPT-5.1".
|
||||
|
||||
You can search for 3 queries in one go, make sure to utilize all 3 queries to maximize the information you can gather. If a question is simple, then split your queries to cover different aspects or related topics to get a comprehensive understanding.
|
||||
If this tool is present and no other tools are more relevant, you MUST use this tool to get the needed information.
|
||||
`;
|
||||
|
||||
const balancedModePrompt = `
|
||||
Use this tool to perform web searches based on the provided queries. This is useful when you need to gather information from the web to answer the user's questions. You can provide up to 3 queries at a time. You will have to use this every single time if this is present and relevant.
|
||||
|
||||
You can call this tool several times if needed to gather enough information.
|
||||
Start initially with broader queries to get an overview, then narrow down with more specific queries based on the results you receive.
|
||||
|
||||
Your queries shouldn't be sentences but rather keywords that are SEO friendly and can be used to search the web for information.
|
||||
|
||||
For example if the user is asking about Tesla, your actions should be like:
|
||||
1. __reasoning_preamble "The user is asking about Tesla. I will start with broader queries to get an overview of Tesla, then narrow down with more specific queries based on the results I receive." then
|
||||
2. web_search ["Tesla", "Tesla latest news", "Tesla stock price"] then
|
||||
3. __reasoning_preamble "Based on the previous search results, I will now narrow down my queries to focus on Tesla's recent developments and stock performance." then
|
||||
4. web_search ["Tesla Q2 2025 earnings", "Tesla new model 2025", "Tesla stock analysis"] then done.
|
||||
5. __reasoning_preamble "I have gathered enough information to provide a comprehensive answer."
|
||||
6. done.
|
||||
|
||||
You can search for 3 queries in one go, make sure to utilize all 3 queries to maximize the information you can gather. If a question is simple, then split your queries to cover different aspects or related topics to get a comprehensive understanding.
|
||||
If this tool is present and no other tools are more relevant, you MUST use this tool to get the needed information. You can call this tools, multiple times as needed.
|
||||
`;
|
||||
|
||||
const qualityModePrompt = `
|
||||
Use this tool to perform web searches based on the provided queries. This is useful when you need to gather information from the web to answer the user's questions. You can provide up to 3 queries at a time. You will have to use this every single time if this is present and relevant.
|
||||
|
||||
You have to call this tool several times to gather enough information unless the question is very simple (like greeting questions or basic facts).
|
||||
Start initially with broader queries to get an overview, then narrow down with more specific queries based on the results you receive.
|
||||
Never stop before at least 5-6 iterations of searches unless the user question is very simple.
|
||||
|
||||
Your queries shouldn't be sentences but rather keywords that are SEO friendly and can be used to search the web for information.
|
||||
|
||||
You can search for 3 queries in one go, make sure to utilize all 3 queries to maximize the information you can gather. If a question is simple, then split your queries to cover different aspects or related topics to get a comprehensive understanding.
|
||||
If this tool is present and no other tools are more relevant, you MUST use this tool to get the needed information. You can call this tools, multiple times as needed.
|
||||
`;
|
||||
|
||||
const webSearchAction: ResearchAction<typeof actionSchema> = {
|
||||
name: 'web_search',
|
||||
schema: actionSchema,
|
||||
getToolDescription: () =>
|
||||
"Use this tool to perform web searches based on the provided queries. This is useful when you need to gather information from the web to answer the user's questions. You can provide up to 3 queries at a time. You will have to use this every single time if this is present and relevant.",
|
||||
getDescription: (config) => {
|
||||
let prompt = '';
|
||||
|
||||
switch (config.mode) {
|
||||
case 'speed':
|
||||
prompt = speedModePrompt;
|
||||
break;
|
||||
case 'balanced':
|
||||
prompt = balancedModePrompt;
|
||||
break;
|
||||
case 'quality':
|
||||
prompt = qualityModePrompt;
|
||||
break;
|
||||
default:
|
||||
prompt = speedModePrompt;
|
||||
break;
|
||||
}
|
||||
|
||||
return prompt;
|
||||
},
|
||||
enabled: (config) =>
|
||||
config.sources.includes('web') &&
|
||||
config.classification.classification.skipSearch === false,
|
||||
execute: async (input, additionalConfig) => {
|
||||
input.queries = input.queries.slice(0, 3);
|
||||
|
||||
const researchBlock = additionalConfig.session.getBlock(
|
||||
additionalConfig.researchBlockId,
|
||||
);
|
||||
|
||||
if (researchBlock && researchBlock.type === 'research') {
|
||||
researchBlock.data.subSteps.push({
|
||||
id: crypto.randomUUID(),
|
||||
type: 'searching',
|
||||
searching: input.queries,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
|
||||
const searchResultsBlockId = crypto.randomUUID();
|
||||
let searchResultsEmitted = false;
|
||||
|
||||
let results: Chunk[] = [];
|
||||
|
||||
const search = async (q: string) => {
|
||||
const res = await searchSearxng(q);
|
||||
|
||||
const resultChunks: Chunk[] = res.results.map((r) => ({
|
||||
content: r.content || r.title,
|
||||
metadata: {
|
||||
title: r.title,
|
||||
url: r.url,
|
||||
},
|
||||
}));
|
||||
|
||||
results.push(...resultChunks);
|
||||
|
||||
if (
|
||||
!searchResultsEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
searchResultsEmitted = true;
|
||||
|
||||
researchBlock.data.subSteps.push({
|
||||
id: searchResultsBlockId,
|
||||
type: 'search_results',
|
||||
reading: resultChunks,
|
||||
});
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
} else if (
|
||||
searchResultsEmitted &&
|
||||
researchBlock &&
|
||||
researchBlock.type === 'research'
|
||||
) {
|
||||
const subStepIndex = researchBlock.data.subSteps.findIndex(
|
||||
(step) => step.id === searchResultsBlockId,
|
||||
);
|
||||
|
||||
const subStep = researchBlock.data.subSteps[
|
||||
subStepIndex
|
||||
] as SearchResultsResearchBlock;
|
||||
|
||||
subStep.reading.push(...resultChunks);
|
||||
|
||||
additionalConfig.session.updateBlock(additionalConfig.researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: researchBlock.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
};
|
||||
|
||||
await Promise.all(input.queries.map(search));
|
||||
|
||||
return {
|
||||
type: 'search_results',
|
||||
results,
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default webSearchAction;
|
||||
225
services/chat-svc/src/lib/agents/search/researcher/index.ts
Normal file
225
services/chat-svc/src/lib/agents/search/researcher/index.ts
Normal file
@@ -0,0 +1,225 @@
|
||||
import { ActionOutput, ResearcherInput, ResearcherOutput } from '../types.js';
|
||||
import { ActionRegistry } from './actions/index.js';
|
||||
import { getResearcherPrompt } from '../../../prompts/search/researcher.js';
|
||||
import SessionManager from '../../../session.js';
|
||||
import { Message, ReasoningResearchBlock } from '../../../types.js';
|
||||
import formatChatHistoryAsString from '../../../utils/formatHistory.js';
|
||||
import { ToolCall } from '../../../models/types.js';
|
||||
|
||||
class Researcher {
|
||||
async research(
|
||||
session: SessionManager,
|
||||
input: ResearcherInput,
|
||||
): Promise<ResearcherOutput> {
|
||||
let actionOutput: ActionOutput[] = [];
|
||||
let maxIteration =
|
||||
input.config.mode === 'speed'
|
||||
? 2
|
||||
: input.config.mode === 'balanced'
|
||||
? 6
|
||||
: 25;
|
||||
|
||||
const availableTools = ActionRegistry.getAvailableActionTools({
|
||||
classification: input.classification,
|
||||
fileIds: input.config.fileIds,
|
||||
mode: input.config.mode,
|
||||
sources: input.config.sources,
|
||||
hasEmbedding: !!input.config.embedding,
|
||||
});
|
||||
|
||||
const availableActionsDescription =
|
||||
ActionRegistry.getAvailableActionsDescriptions({
|
||||
classification: input.classification,
|
||||
fileIds: input.config.fileIds,
|
||||
mode: input.config.mode,
|
||||
sources: input.config.sources,
|
||||
hasEmbedding: !!input.config.embedding,
|
||||
});
|
||||
|
||||
const researchBlockId = crypto.randomUUID();
|
||||
|
||||
session.emitBlock({
|
||||
id: researchBlockId,
|
||||
type: 'research',
|
||||
data: {
|
||||
subSteps: [],
|
||||
},
|
||||
});
|
||||
|
||||
const agentMessageHistory: Message[] = [
|
||||
{
|
||||
role: 'user',
|
||||
content: `
|
||||
<conversation>
|
||||
${formatChatHistoryAsString(input.chatHistory.slice(-10))}
|
||||
User: ${input.followUp} (Standalone question: ${input.classification.standaloneFollowUp})
|
||||
</conversation>
|
||||
`,
|
||||
},
|
||||
];
|
||||
|
||||
for (let i = 0; i < maxIteration; i++) {
|
||||
const researcherPrompt = getResearcherPrompt(
|
||||
availableActionsDescription,
|
||||
input.config.mode,
|
||||
i,
|
||||
maxIteration,
|
||||
input.config.fileIds,
|
||||
input.config.locale,
|
||||
);
|
||||
|
||||
const actionStream = input.config.llm.streamText({
|
||||
messages: [
|
||||
{
|
||||
role: 'system',
|
||||
content: researcherPrompt,
|
||||
},
|
||||
...agentMessageHistory,
|
||||
],
|
||||
tools: availableTools,
|
||||
});
|
||||
|
||||
const block = session.getBlock(researchBlockId);
|
||||
|
||||
let reasoningEmitted = false;
|
||||
let reasoningId = crypto.randomUUID();
|
||||
|
||||
let finalToolCalls: ToolCall[] = [];
|
||||
|
||||
for await (const partialRes of actionStream) {
|
||||
if (partialRes.toolCallChunk.length > 0) {
|
||||
partialRes.toolCallChunk.forEach((tc) => {
|
||||
if (
|
||||
tc.name === '__reasoning_preamble' &&
|
||||
tc.arguments['plan'] &&
|
||||
!reasoningEmitted &&
|
||||
block &&
|
||||
block.type === 'research'
|
||||
) {
|
||||
reasoningEmitted = true;
|
||||
|
||||
block.data.subSteps.push({
|
||||
id: reasoningId,
|
||||
type: 'reasoning',
|
||||
reasoning: tc.arguments['plan'],
|
||||
});
|
||||
|
||||
session.updateBlock(researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: block.data.subSteps,
|
||||
},
|
||||
]);
|
||||
} else if (
|
||||
tc.name === '__reasoning_preamble' &&
|
||||
tc.arguments['plan'] &&
|
||||
reasoningEmitted &&
|
||||
block &&
|
||||
block.type === 'research'
|
||||
) {
|
||||
const subStepIndex = block.data.subSteps.findIndex(
|
||||
(step: any) => step.id === reasoningId,
|
||||
);
|
||||
|
||||
if (subStepIndex !== -1) {
|
||||
const subStep = block.data.subSteps[
|
||||
subStepIndex
|
||||
] as ReasoningResearchBlock;
|
||||
subStep.reasoning = tc.arguments['plan'];
|
||||
session.updateBlock(researchBlockId, [
|
||||
{
|
||||
op: 'replace',
|
||||
path: '/data/subSteps',
|
||||
value: block.data.subSteps,
|
||||
},
|
||||
]);
|
||||
}
|
||||
}
|
||||
|
||||
const existingIndex = finalToolCalls.findIndex(
|
||||
(ftc) => ftc.id === tc.id,
|
||||
);
|
||||
|
||||
if (existingIndex !== -1) {
|
||||
finalToolCalls[existingIndex].arguments = tc.arguments;
|
||||
} else {
|
||||
finalToolCalls.push(tc);
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
if (finalToolCalls.length === 0) {
|
||||
break;
|
||||
}
|
||||
|
||||
if (finalToolCalls[finalToolCalls.length - 1].name === 'done') {
|
||||
break;
|
||||
}
|
||||
|
||||
agentMessageHistory.push({
|
||||
role: 'assistant',
|
||||
content: '',
|
||||
tool_calls: finalToolCalls,
|
||||
});
|
||||
|
||||
const actionResults = await ActionRegistry.executeAll(finalToolCalls, {
|
||||
llm: input.config.llm,
|
||||
embedding: input.config.embedding,
|
||||
session: session,
|
||||
researchBlockId: researchBlockId,
|
||||
fileIds: input.config.fileIds,
|
||||
});
|
||||
|
||||
actionOutput.push(...actionResults);
|
||||
|
||||
actionResults.forEach((action, i) => {
|
||||
agentMessageHistory.push({
|
||||
role: 'tool',
|
||||
id: finalToolCalls[i].id,
|
||||
name: finalToolCalls[i].name,
|
||||
content: JSON.stringify(action),
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
const searchResults = actionOutput
|
||||
.filter((a) => a.type === 'search_results')
|
||||
.flatMap((a) => a.results);
|
||||
|
||||
const seenUrls = new Map<string, number>();
|
||||
|
||||
const filteredSearchResults = searchResults
|
||||
.map((result, index) => {
|
||||
if (result.metadata?.url as string && !seenUrls.has(result.metadata?.url as string)) {
|
||||
seenUrls.set(result.metadata?.url as string, index);
|
||||
return result;
|
||||
} else if (result.metadata?.url as string && seenUrls.has(result.metadata?.url as string)) {
|
||||
const existingIndex = seenUrls.get(result.metadata?.url as string)!;
|
||||
|
||||
const existingResult = searchResults[existingIndex];
|
||||
|
||||
existingResult.content += `\n\n${result.content}`;
|
||||
|
||||
return undefined;
|
||||
}
|
||||
|
||||
return result;
|
||||
})
|
||||
.filter((r) => r !== undefined);
|
||||
|
||||
session.emitBlock({
|
||||
id: crypto.randomUUID(),
|
||||
type: 'source',
|
||||
data: filteredSearchResults,
|
||||
});
|
||||
|
||||
return {
|
||||
findings: actionOutput,
|
||||
searchFindings: filteredSearchResults,
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
export default Researcher;
|
||||
141
services/chat-svc/src/lib/agents/search/types.ts
Normal file
141
services/chat-svc/src/lib/agents/search/types.ts
Normal file
@@ -0,0 +1,141 @@
|
||||
import z from 'zod';
|
||||
import BaseLLM from '../../models/base/llm.js';
|
||||
import BaseEmbedding from '../../models/base/embedding.js';
|
||||
import SessionManager from '../../session.js';
|
||||
import { ChatTurnMessage, Chunk } from '../../types.js';
|
||||
|
||||
export type SearchSources = 'web' | 'discussions' | 'academic';
|
||||
|
||||
/** Answer mode — вертикаль ответа (travel, finance, academic и т.д.) */
|
||||
export type AnswerMode = 'standard' | 'focus' | 'academic' | 'writing' | 'travel' | 'finance';
|
||||
|
||||
/** locale по geo (например ru, en) — язык ответа */
|
||||
export type SearchAgentConfig = {
|
||||
sources: SearchSources[];
|
||||
fileIds: string[];
|
||||
llm: BaseLLM<any>;
|
||||
embedding: BaseEmbedding<any> | null;
|
||||
mode: 'speed' | 'balanced' | 'quality';
|
||||
systemInstructions: string;
|
||||
locale?: string;
|
||||
/** Memory context from memory-svc (Pro) — user preferences, facts */
|
||||
memoryContext?: string;
|
||||
/** Answer mode — vertical focus (travel, finance, academic) */
|
||||
answerMode?: AnswerMode;
|
||||
/** Response preferences from user settings */
|
||||
responsePrefs?: { format?: string; length?: string; tone?: string };
|
||||
/** Step-by-step Learning — объяснять пошагово, показывать ход мысли */
|
||||
learningMode?: boolean;
|
||||
/** Model Council (Max): 3 LLMs for parallel writer + synthesis */
|
||||
councilLlms?: [BaseLLM<any>, BaseLLM<any>, BaseLLM<any>];
|
||||
/** Library client для сохранения messages (вместо SQLite) */
|
||||
libraryClient?: { upsertMessage: (threadId: string, msgId: string, query: string, opts?: object) => Promise<void>; updateMessage: (threadId: string, msgId: string, opts: object) => Promise<void>; enabled: boolean };
|
||||
};
|
||||
|
||||
export type SearchAgentInput = {
|
||||
chatHistory: ChatTurnMessage[];
|
||||
followUp: string;
|
||||
config: SearchAgentConfig;
|
||||
chatId: string;
|
||||
messageId: string;
|
||||
};
|
||||
|
||||
export type WidgetInput = {
|
||||
chatHistory: ChatTurnMessage[];
|
||||
followUp: string;
|
||||
classification: ClassifierOutput;
|
||||
llm: BaseLLM<any>;
|
||||
};
|
||||
|
||||
export type Widget = {
|
||||
type: string;
|
||||
shouldExecute: (classification: ClassifierOutput) => boolean;
|
||||
execute: (input: WidgetInput) => Promise<WidgetOutput | void>;
|
||||
};
|
||||
|
||||
export type WidgetOutput = {
|
||||
type: string;
|
||||
llmContext: string;
|
||||
data: any;
|
||||
};
|
||||
|
||||
export type ClassifierInput = {
|
||||
llm: BaseLLM<any>;
|
||||
enabledSources: SearchSources[];
|
||||
query: string;
|
||||
chatHistory: ChatTurnMessage[];
|
||||
locale?: string;
|
||||
};
|
||||
|
||||
export type ClassifierOutput = {
|
||||
classification: {
|
||||
skipSearch: boolean;
|
||||
personalSearch: boolean;
|
||||
academicSearch: boolean;
|
||||
discussionSearch: boolean;
|
||||
showWeatherWidget: boolean;
|
||||
showStockWidget: boolean;
|
||||
showCalculationWidget: boolean;
|
||||
};
|
||||
standaloneFollowUp: string;
|
||||
};
|
||||
|
||||
export type AdditionalConfig = {
|
||||
llm: BaseLLM<any>;
|
||||
embedding: BaseEmbedding<any> | null;
|
||||
session: SessionManager;
|
||||
};
|
||||
|
||||
export type ResearcherInput = {
|
||||
chatHistory: ChatTurnMessage[];
|
||||
followUp: string;
|
||||
classification: ClassifierOutput;
|
||||
config: SearchAgentConfig;
|
||||
};
|
||||
|
||||
export type ResearcherOutput = {
|
||||
findings: ActionOutput[];
|
||||
searchFindings: Chunk[];
|
||||
};
|
||||
|
||||
export type SearchActionOutput = {
|
||||
type: 'search_results';
|
||||
results: Chunk[];
|
||||
};
|
||||
|
||||
export type DoneActionOutput = {
|
||||
type: 'done';
|
||||
};
|
||||
|
||||
export type ReasoningResearchAction = {
|
||||
type: 'reasoning';
|
||||
reasoning: string;
|
||||
};
|
||||
|
||||
export type ActionOutput =
|
||||
| SearchActionOutput
|
||||
| DoneActionOutput
|
||||
| ReasoningResearchAction;
|
||||
|
||||
export interface ResearchAction<
|
||||
TSchema extends z.ZodObject<any> = z.ZodObject<any>,
|
||||
> {
|
||||
name: string;
|
||||
schema: z.ZodObject<any>;
|
||||
getToolDescription: (config: { mode: SearchAgentConfig['mode'] }) => string;
|
||||
getDescription: (config: { mode: SearchAgentConfig['mode'] }) => string;
|
||||
enabled: (config: {
|
||||
classification: ClassifierOutput;
|
||||
fileIds: string[];
|
||||
mode: SearchAgentConfig['mode'];
|
||||
sources: SearchSources[];
|
||||
hasEmbedding?: boolean;
|
||||
}) => boolean;
|
||||
execute: (
|
||||
params: z.infer<TSchema>,
|
||||
additionalConfig: AdditionalConfig & {
|
||||
researchBlockId: string;
|
||||
fileIds: string[];
|
||||
},
|
||||
) => Promise<ActionOutput>;
|
||||
}
|
||||
@@ -0,0 +1,71 @@
|
||||
import z from 'zod';
|
||||
import { Widget } from '../types.js';
|
||||
import formatChatHistoryAsString from '../../../utils/formatHistory.js';
|
||||
import { exp, evaluate as mathEval } from 'mathjs';
|
||||
|
||||
const schema = z.object({
|
||||
expression: z
|
||||
.string()
|
||||
.describe('Mathematical expression to calculate or evaluate.'),
|
||||
notPresent: z
|
||||
.boolean()
|
||||
.describe('Whether there is any need for the calculation widget.'),
|
||||
});
|
||||
|
||||
const system = `
|
||||
<role>
|
||||
Assistant is a calculation expression extractor. You will recieve a user follow up and a conversation history.
|
||||
Your task is to determine if there is a mathematical expression that needs to be calculated or evaluated. If there is, extract the expression and return it. If there is no need for any calculation, set notPresent to true.
|
||||
</role>
|
||||
|
||||
<instructions>
|
||||
Make sure that the extracted expression is valid and can be used to calculate the result with Math JS library (https://mathjs.org/). If the expression is not valid, set notPresent to true.
|
||||
If you feel like you cannot extract a valid expression, set notPresent to true.
|
||||
</instructions>
|
||||
|
||||
<output_format>
|
||||
You must respond in the following JSON format without any extra text, explanations or filler sentences:
|
||||
{
|
||||
"expression": string,
|
||||
"notPresent": boolean
|
||||
}
|
||||
</output_format>
|
||||
`;
|
||||
|
||||
const calculationWidget: Widget = {
|
||||
type: 'calculationWidget',
|
||||
shouldExecute: (classification) =>
|
||||
classification.classification.showCalculationWidget,
|
||||
execute: async (input) => {
|
||||
const output = await input.llm.generateObject<typeof schema>({
|
||||
messages: [
|
||||
{
|
||||
role: 'system',
|
||||
content: system,
|
||||
},
|
||||
{
|
||||
role: 'user',
|
||||
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_follow_up>\n${input.followUp}\n</user_follow_up>`,
|
||||
},
|
||||
],
|
||||
schema,
|
||||
});
|
||||
|
||||
if (output.notPresent) {
|
||||
return;
|
||||
}
|
||||
|
||||
const result = mathEval(output.expression);
|
||||
|
||||
return {
|
||||
type: 'calculation_result',
|
||||
llmContext: `The result of the calculation for the expression "${output.expression}" is: ${result}`,
|
||||
data: {
|
||||
expression: output.expression,
|
||||
result,
|
||||
},
|
||||
};
|
||||
},
|
||||
};
|
||||
|
||||
export default calculationWidget;
|
||||
36
services/chat-svc/src/lib/agents/search/widgets/executor.ts
Normal file
36
services/chat-svc/src/lib/agents/search/widgets/executor.ts
Normal file
@@ -0,0 +1,36 @@
|
||||
import { Widget, WidgetInput, WidgetOutput } from '../types.js';
|
||||
|
||||
class WidgetExecutor {
|
||||
static widgets = new Map<string, Widget>();
|
||||
|
||||
static register(widget: Widget) {
|
||||
this.widgets.set(widget.type, widget);
|
||||
}
|
||||
|
||||
static getWidget(type: string): Widget | undefined {
|
||||
return this.widgets.get(type);
|
||||
}
|
||||
|
||||
static async executeAll(input: WidgetInput): Promise<WidgetOutput[]> {
|
||||
const results: WidgetOutput[] = [];
|
||||
|
||||
await Promise.all(
|
||||
Array.from(this.widgets.values()).map(async (widget) => {
|
||||
try {
|
||||
if (widget.shouldExecute(input.classification)) {
|
||||
const output = await widget.execute(input);
|
||||
if (output) {
|
||||
results.push(output);
|
||||
}
|
||||
}
|
||||
} catch (e) {
|
||||
console.log(`Error executing widget ${widget.type}:`, e);
|
||||
}
|
||||
}),
|
||||
);
|
||||
|
||||
return results;
|
||||
}
|
||||
}
|
||||
|
||||
export default WidgetExecutor;
|
||||
10
services/chat-svc/src/lib/agents/search/widgets/index.ts
Normal file
10
services/chat-svc/src/lib/agents/search/widgets/index.ts
Normal file
@@ -0,0 +1,10 @@
|
||||
import calculationWidget from './calculationWidget.js';
|
||||
import WidgetExecutor from './executor.js';
|
||||
import weatherWidget from './weatherWidget.js';
|
||||
import stockWidget from './stockWidget.js';
|
||||
|
||||
WidgetExecutor.register(weatherWidget);
|
||||
WidgetExecutor.register(calculationWidget);
|
||||
WidgetExecutor.register(stockWidget);
|
||||
|
||||
export { WidgetExecutor };
|
||||
434
services/chat-svc/src/lib/agents/search/widgets/stockWidget.ts
Normal file
434
services/chat-svc/src/lib/agents/search/widgets/stockWidget.ts
Normal file
@@ -0,0 +1,434 @@
|
||||
import z from 'zod';
|
||||
import { Widget } from '../types.js';
|
||||
import YahooFinance from 'yahoo-finance2';
|
||||
import formatChatHistoryAsString from '../../../utils/formatHistory.js';
|
||||
|
||||
const yf = new YahooFinance({
|
||||
suppressNotices: ['yahooSurvey'],
|
||||
});
|
||||
|
||||
const schema = z.object({
|
||||
name: z
|
||||
.string()
|
||||
.describe(
|
||||
"The stock name for example Nvidia, Google, Apple, Microsoft etc. You can also return ticker if you're aware of it otherwise just use the name.",
|
||||
),
|
||||
comparisonNames: z
|
||||
.array(z.string())
|
||||
.max(3)
|
||||
.describe(
|
||||
"Optional array of up to 3 stock names to compare against the base name (e.g., ['Microsoft', 'GOOGL', 'Meta']). Charts will show percentage change comparison.",
|
||||
),
|
||||
notPresent: z
|
||||
.boolean()
|
||||
.describe('Whether there is no need for the stock widget.'),
|
||||
});
|
||||
|
||||
const systemPrompt = `
|
||||
<role>
|
||||
You are a stock ticker/name extractor. You will receive a user follow up and a conversation history.
|
||||
Your task is to determine if the user is asking about stock information and extract the stock name(s) they want data for.
|
||||
</role>
|
||||
|
||||
<instructions>
|
||||
- If the user is asking about a stock, extract the primary stock name or ticker.
|
||||
- If the user wants to compare stocks, extract up to 3 comparison stock names in comparisonNames.
|
||||
- You can use either stock names (e.g., "Nvidia", "Apple") or tickers (e.g., "NVDA", "AAPL").
|
||||
- If you cannot determine a valid stock or the query is not stock-related, set notPresent to true.
|
||||
- If no comparison is needed, set comparisonNames to an empty array.
|
||||
</instructions>
|
||||
|
||||
<output_format>
|
||||
You must respond in the following JSON format without any extra text, explanations or filler sentences:
|
||||
{
|
||||
"name": string,
|
||||
"comparisonNames": string[],
|
||||
"notPresent": boolean
|
||||
}
|
||||
</output_format>
|
||||
`;
|
||||
|
||||
const stockWidget: Widget = {
|
||||
type: 'stockWidget',
|
||||
shouldExecute: (classification) =>
|
||||
classification.classification.showStockWidget,
|
||||
execute: async (input) => {
|
||||
const output = await input.llm.generateObject<typeof schema>({
|
||||
messages: [
|
||||
{
|
||||
role: 'system',
|
||||
content: systemPrompt,
|
||||
},
|
||||
{
|
||||
role: 'user',
|
||||
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_follow_up>\n${input.followUp}\n</user_follow_up>`,
|
||||
},
|
||||
],
|
||||
schema,
|
||||
});
|
||||
|
||||
if (output.notPresent) {
|
||||
return;
|
||||
}
|
||||
|
||||
const params = output;
|
||||
try {
|
||||
const name = params.name;
|
||||
|
||||
const findings = await yf.search(name);
|
||||
|
||||
if (findings.quotes.length === 0)
|
||||
throw new Error(`Failed to find quote for name/symbol: ${name}`);
|
||||
|
||||
const ticker = findings.quotes[0].symbol as string;
|
||||
|
||||
const quote: any = await yf.quote(ticker);
|
||||
|
||||
const chartPromises = {
|
||||
'1D': yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 2 * 24 * 60 * 60 * 1000),
|
||||
period2: new Date(),
|
||||
interval: '5m',
|
||||
})
|
||||
.catch(() => null),
|
||||
'5D': yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 6 * 24 * 60 * 60 * 1000),
|
||||
period2: new Date(),
|
||||
interval: '15m',
|
||||
})
|
||||
.catch(() => null),
|
||||
'1M': yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
'3M': yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 90 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
'6M': yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 180 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
'1Y': yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 365 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
MAX: yf
|
||||
.chart(ticker, {
|
||||
period1: new Date(Date.now() - 10 * 365 * 24 * 60 * 60 * 1000),
|
||||
interval: '1wk',
|
||||
})
|
||||
.catch(() => null),
|
||||
};
|
||||
|
||||
const charts = await Promise.all([
|
||||
chartPromises['1D'],
|
||||
chartPromises['5D'],
|
||||
chartPromises['1M'],
|
||||
chartPromises['3M'],
|
||||
chartPromises['6M'],
|
||||
chartPromises['1Y'],
|
||||
chartPromises['MAX'],
|
||||
]);
|
||||
|
||||
const [chart1D, chart5D, chart1M, chart3M, chart6M, chart1Y, chartMAX] =
|
||||
charts;
|
||||
|
||||
if (!quote) {
|
||||
throw new Error(`No data found for ticker: ${ticker}`);
|
||||
}
|
||||
|
||||
let comparisonData: any = null;
|
||||
if (params.comparisonNames.length > 0) {
|
||||
const comparisonPromises = params.comparisonNames
|
||||
.slice(0, 3)
|
||||
.map(async (compName) => {
|
||||
try {
|
||||
const compFindings = await yf.search(compName);
|
||||
|
||||
if (compFindings.quotes.length === 0) return null;
|
||||
|
||||
const compTicker = compFindings.quotes[0].symbol as string;
|
||||
const compQuote = await yf.quote(compTicker);
|
||||
const compCharts = await Promise.all([
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(Date.now() - 2 * 24 * 60 * 60 * 1000),
|
||||
period2: new Date(),
|
||||
interval: '5m',
|
||||
})
|
||||
.catch(() => null),
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(Date.now() - 6 * 24 * 60 * 60 * 1000),
|
||||
period2: new Date(),
|
||||
interval: '15m',
|
||||
})
|
||||
.catch(() => null),
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(Date.now() - 30 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(Date.now() - 90 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(Date.now() - 180 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(Date.now() - 365 * 24 * 60 * 60 * 1000),
|
||||
interval: '1d',
|
||||
})
|
||||
.catch(() => null),
|
||||
yf
|
||||
.chart(compTicker, {
|
||||
period1: new Date(
|
||||
Date.now() - 10 * 365 * 24 * 60 * 60 * 1000,
|
||||
),
|
||||
interval: '1wk',
|
||||
})
|
||||
.catch(() => null),
|
||||
]);
|
||||
return {
|
||||
ticker: compTicker,
|
||||
name: compQuote.shortName || compTicker,
|
||||
charts: compCharts,
|
||||
};
|
||||
} catch (error) {
|
||||
console.error(
|
||||
`Failed to fetch comparison ticker ${compName}:`,
|
||||
error,
|
||||
);
|
||||
return null;
|
||||
}
|
||||
});
|
||||
const compResults = await Promise.all(comparisonPromises);
|
||||
comparisonData = compResults.filter((r) => r !== null);
|
||||
}
|
||||
|
||||
const stockData = {
|
||||
symbol: quote.symbol,
|
||||
shortName: quote.shortName || quote.longName || ticker,
|
||||
longName: quote.longName,
|
||||
exchange: quote.fullExchangeName || quote.exchange,
|
||||
currency: quote.currency,
|
||||
quoteType: quote.quoteType,
|
||||
|
||||
marketState: quote.marketState,
|
||||
regularMarketTime: quote.regularMarketTime,
|
||||
postMarketTime: quote.postMarketTime,
|
||||
preMarketTime: quote.preMarketTime,
|
||||
|
||||
regularMarketPrice: quote.regularMarketPrice,
|
||||
regularMarketChange: quote.regularMarketChange,
|
||||
regularMarketChangePercent: quote.regularMarketChangePercent,
|
||||
regularMarketPreviousClose: quote.regularMarketPreviousClose,
|
||||
regularMarketOpen: quote.regularMarketOpen,
|
||||
regularMarketDayHigh: quote.regularMarketDayHigh,
|
||||
regularMarketDayLow: quote.regularMarketDayLow,
|
||||
|
||||
postMarketPrice: quote.postMarketPrice,
|
||||
postMarketChange: quote.postMarketChange,
|
||||
postMarketChangePercent: quote.postMarketChangePercent,
|
||||
preMarketPrice: quote.preMarketPrice,
|
||||
preMarketChange: quote.preMarketChange,
|
||||
preMarketChangePercent: quote.preMarketChangePercent,
|
||||
|
||||
regularMarketVolume: quote.regularMarketVolume,
|
||||
averageDailyVolume3Month: quote.averageDailyVolume3Month,
|
||||
averageDailyVolume10Day: quote.averageDailyVolume10Day,
|
||||
bid: quote.bid,
|
||||
bidSize: quote.bidSize,
|
||||
ask: quote.ask,
|
||||
askSize: quote.askSize,
|
||||
|
||||
fiftyTwoWeekLow: quote.fiftyTwoWeekLow,
|
||||
fiftyTwoWeekHigh: quote.fiftyTwoWeekHigh,
|
||||
fiftyTwoWeekChange: quote.fiftyTwoWeekChange,
|
||||
fiftyTwoWeekChangePercent: quote.fiftyTwoWeekChangePercent,
|
||||
|
||||
marketCap: quote.marketCap,
|
||||
trailingPE: quote.trailingPE,
|
||||
forwardPE: quote.forwardPE,
|
||||
priceToBook: quote.priceToBook,
|
||||
bookValue: quote.bookValue,
|
||||
earningsPerShare: quote.epsTrailingTwelveMonths,
|
||||
epsForward: quote.epsForward,
|
||||
|
||||
dividendRate: quote.dividendRate,
|
||||
dividendYield: quote.dividendYield,
|
||||
exDividendDate: quote.exDividendDate,
|
||||
trailingAnnualDividendRate: quote.trailingAnnualDividendRate,
|
||||
trailingAnnualDividendYield: quote.trailingAnnualDividendYield,
|
||||
|
||||
beta: quote.beta,
|
||||
|
||||
fiftyDayAverage: quote.fiftyDayAverage,
|
||||
fiftyDayAverageChange: quote.fiftyDayAverageChange,
|
||||
fiftyDayAverageChangePercent: quote.fiftyDayAverageChangePercent,
|
||||
twoHundredDayAverage: quote.twoHundredDayAverage,
|
||||
twoHundredDayAverageChange: quote.twoHundredDayAverageChange,
|
||||
twoHundredDayAverageChangePercent:
|
||||
quote.twoHundredDayAverageChangePercent,
|
||||
|
||||
sector: quote.sector,
|
||||
industry: quote.industry,
|
||||
website: quote.website,
|
||||
|
||||
chartData: {
|
||||
'1D': chart1D
|
||||
? {
|
||||
timestamps: chart1D.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chart1D.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'5D': chart5D
|
||||
? {
|
||||
timestamps: chart5D.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chart5D.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'1M': chart1M
|
||||
? {
|
||||
timestamps: chart1M.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chart1M.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'3M': chart3M
|
||||
? {
|
||||
timestamps: chart3M.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chart3M.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'6M': chart6M
|
||||
? {
|
||||
timestamps: chart6M.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chart6M.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'1Y': chart1Y
|
||||
? {
|
||||
timestamps: chart1Y.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chart1Y.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
MAX: chartMAX
|
||||
? {
|
||||
timestamps: chartMAX.quotes.map((q: any) => q.date.getTime()),
|
||||
prices: chartMAX.quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
},
|
||||
comparisonData: comparisonData
|
||||
? comparisonData.map((comp: any) => ({
|
||||
ticker: comp.ticker,
|
||||
name: comp.name,
|
||||
chartData: {
|
||||
'1D': comp.charts[0]
|
||||
? {
|
||||
timestamps: comp.charts[0].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[0].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'5D': comp.charts[1]
|
||||
? {
|
||||
timestamps: comp.charts[1].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[1].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'1M': comp.charts[2]
|
||||
? {
|
||||
timestamps: comp.charts[2].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[2].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'3M': comp.charts[3]
|
||||
? {
|
||||
timestamps: comp.charts[3].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[3].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'6M': comp.charts[4]
|
||||
? {
|
||||
timestamps: comp.charts[4].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[4].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
'1Y': comp.charts[5]
|
||||
? {
|
||||
timestamps: comp.charts[5].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[5].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
MAX: comp.charts[6]
|
||||
? {
|
||||
timestamps: comp.charts[6].quotes.map((q: any) =>
|
||||
q.date.getTime(),
|
||||
),
|
||||
prices: comp.charts[6].quotes.map((q: any) => q.close),
|
||||
}
|
||||
: null,
|
||||
},
|
||||
}))
|
||||
: null,
|
||||
};
|
||||
|
||||
return {
|
||||
type: 'stock',
|
||||
llmContext: `Current price of ${stockData.shortName} (${stockData.symbol}) is ${stockData.regularMarketPrice} ${stockData.currency}. Other details: ${JSON.stringify(
|
||||
{
|
||||
marketState: stockData.marketState,
|
||||
regularMarketChange: stockData.regularMarketChange,
|
||||
regularMarketChangePercent: stockData.regularMarketChangePercent,
|
||||
marketCap: stockData.marketCap,
|
||||
peRatio: stockData.trailingPE,
|
||||
dividendYield: stockData.dividendYield,
|
||||
},
|
||||
)}`,
|
||||
data: stockData,
|
||||
};
|
||||
} catch (error: any) {
|
||||
return {
|
||||
type: 'stock',
|
||||
llmContext: 'Failed to fetch stock data.',
|
||||
data: {
|
||||
error: `Error fetching stock data: ${error.message || error}`,
|
||||
ticker: params.name,
|
||||
},
|
||||
};
|
||||
}
|
||||
},
|
||||
};
|
||||
|
||||
export default stockWidget;
|
||||
203
services/chat-svc/src/lib/agents/search/widgets/weatherWidget.ts
Normal file
203
services/chat-svc/src/lib/agents/search/widgets/weatherWidget.ts
Normal file
@@ -0,0 +1,203 @@
|
||||
import z from 'zod';
|
||||
import { Widget } from '../types.js';
|
||||
import formatChatHistoryAsString from '../../../utils/formatHistory.js';
|
||||
|
||||
const schema = z.object({
|
||||
location: z
|
||||
.string()
|
||||
.describe(
|
||||
'Human-readable location name (e.g., "New York, NY, USA", "London, UK"). Use this OR lat/lon coordinates, never both. Leave empty string if providing coordinates.',
|
||||
),
|
||||
lat: z
|
||||
.number()
|
||||
.describe(
|
||||
'Latitude coordinate in decimal degrees (e.g., 40.7128). Only use when location name is empty.',
|
||||
),
|
||||
lon: z
|
||||
.number()
|
||||
.describe(
|
||||
'Longitude coordinate in decimal degrees (e.g., -74.0060). Only use when location name is empty.',
|
||||
),
|
||||
notPresent: z
|
||||
.boolean()
|
||||
.describe('Whether there is no need for the weather widget.'),
|
||||
});
|
||||
|
||||
const systemPrompt = `
|
||||
<role>
|
||||
You are a location extractor for weather queries. You will receive a user follow up and a conversation history.
|
||||
Your task is to determine if the user is asking about weather and extract the location they want weather for.
|
||||
</role>
|
||||
|
||||
<instructions>
|
||||
- If the user is asking about weather, extract the location name OR coordinates (never both).
|
||||
- If using location name, set lat and lon to 0.
|
||||
- If using coordinates, set location to empty string.
|
||||
- If you cannot determine a valid location or the query is not weather-related, set notPresent to true.
|
||||
- Location should be specific (city, state/region, country) for best results.
|
||||
- You have to give the location so that it can be used to fetch weather data, it cannot be left empty unless notPresent is true.
|
||||
- Make sure to infer short forms of location names (e.g., "NYC" -> "New York City", "LA" -> "Los Angeles").
|
||||
</instructions>
|
||||
|
||||
<output_format>
|
||||
You must respond in the following JSON format without any extra text, explanations or filler sentences:
|
||||
{
|
||||
"location": string,
|
||||
"lat": number,
|
||||
"lon": number,
|
||||
"notPresent": boolean
|
||||
}
|
||||
</output_format>
|
||||
`;
|
||||
|
||||
const weatherWidget: Widget = {
|
||||
type: 'weatherWidget',
|
||||
shouldExecute: (classification) =>
|
||||
classification.classification.showWeatherWidget,
|
||||
execute: async (input) => {
|
||||
const output = await input.llm.generateObject<typeof schema>({
|
||||
messages: [
|
||||
{
|
||||
role: 'system',
|
||||
content: systemPrompt,
|
||||
},
|
||||
{
|
||||
role: 'user',
|
||||
content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_follow_up>\n${input.followUp}\n</user_follow_up>`,
|
||||
},
|
||||
],
|
||||
schema,
|
||||
});
|
||||
|
||||
if (output.notPresent) {
|
||||
return;
|
||||
}
|
||||
|
||||
const params = output;
|
||||
|
||||
try {
|
||||
if (
|
||||
params.location === '' &&
|
||||
(params.lat === undefined || params.lon === undefined)
|
||||
) {
|
||||
throw new Error(
|
||||
'Either location name or both latitude and longitude must be provided.',
|
||||
);
|
||||
}
|
||||
|
||||
if (params.location !== '') {
|
||||
const openStreetMapUrl = `https://nominatim.openstreetmap.org/search?q=${encodeURIComponent(params.location)}&format=json&limit=1`;
|
||||
|
||||
const locationRes = await fetch(openStreetMapUrl, {
|
||||
headers: {
|
||||
'User-Agent': 'GooSeek',
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
});
|
||||
|
||||
const data = await locationRes.json();
|
||||
|
||||
const location = data[0];
|
||||
|
||||
if (!location) {
|
||||
throw new Error(
|
||||
`Could not find coordinates for location: ${params.location}`,
|
||||
);
|
||||
}
|
||||
|
||||
const weatherRes = await fetch(
|
||||
`https://api.open-meteo.com/v1/forecast?latitude=${location.lat}&longitude=${location.lon}¤t=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
|
||||
{
|
||||
headers: {
|
||||
'User-Agent': 'GooSeek',
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
);
|
||||
|
||||
const weatherData = await weatherRes.json();
|
||||
|
||||
return {
|
||||
type: 'weather',
|
||||
llmContext: `Weather in ${params.location} is ${JSON.stringify(weatherData.current)}`,
|
||||
data: {
|
||||
location: params.location,
|
||||
latitude: location.lat,
|
||||
longitude: location.lon,
|
||||
current: weatherData.current,
|
||||
hourly: {
|
||||
time: weatherData.hourly.time.slice(0, 24),
|
||||
temperature_2m: weatherData.hourly.temperature_2m.slice(0, 24),
|
||||
precipitation_probability:
|
||||
weatherData.hourly.precipitation_probability.slice(0, 24),
|
||||
precipitation: weatherData.hourly.precipitation.slice(0, 24),
|
||||
weather_code: weatherData.hourly.weather_code.slice(0, 24),
|
||||
},
|
||||
daily: weatherData.daily,
|
||||
timezone: weatherData.timezone,
|
||||
},
|
||||
};
|
||||
} else if (params.lat !== undefined && params.lon !== undefined) {
|
||||
const [weatherRes, locationRes] = await Promise.all([
|
||||
fetch(
|
||||
`https://api.open-meteo.com/v1/forecast?latitude=${params.lat}&longitude=${params.lon}¤t=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
|
||||
{
|
||||
headers: {
|
||||
'User-Agent': 'GooSeek',
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
),
|
||||
fetch(
|
||||
`https://nominatim.openstreetmap.org/reverse?lat=${params.lat}&lon=${params.lon}&format=json`,
|
||||
{
|
||||
headers: {
|
||||
'User-Agent': 'GooSeek',
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
},
|
||||
),
|
||||
]);
|
||||
|
||||
const weatherData = await weatherRes.json();
|
||||
const locationData = await locationRes.json();
|
||||
|
||||
return {
|
||||
type: 'weather',
|
||||
llmContext: `Weather in ${locationData.display_name} is ${JSON.stringify(weatherData.current)}`,
|
||||
data: {
|
||||
location: locationData.display_name,
|
||||
latitude: params.lat,
|
||||
longitude: params.lon,
|
||||
current: weatherData.current,
|
||||
hourly: {
|
||||
time: weatherData.hourly.time.slice(0, 24),
|
||||
temperature_2m: weatherData.hourly.temperature_2m.slice(0, 24),
|
||||
precipitation_probability:
|
||||
weatherData.hourly.precipitation_probability.slice(0, 24),
|
||||
precipitation: weatherData.hourly.precipitation.slice(0, 24),
|
||||
weather_code: weatherData.hourly.weather_code.slice(0, 24),
|
||||
},
|
||||
daily: weatherData.daily,
|
||||
timezone: weatherData.timezone,
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
return {
|
||||
type: 'weather',
|
||||
llmContext: 'No valid location or coordinates provided.',
|
||||
data: null,
|
||||
};
|
||||
} catch (err) {
|
||||
return {
|
||||
type: 'weather',
|
||||
llmContext: 'Failed to fetch weather data.',
|
||||
data: {
|
||||
error: `Error fetching weather data: ${err}`,
|
||||
},
|
||||
};
|
||||
}
|
||||
},
|
||||
};
|
||||
export default weatherWidget;
|
||||
Reference in New Issue
Block a user