feat: монорепо миграция, Discover/SearxNG улучшения

- Миграция на монорепозиторий (apps/frontend, apps/chat-service, etc.)
- Discover: проверка SearxNG, понятное empty state при ненастроенном поиске
- searxng.ts: валидация URL, проверка JSON-ответа, авто-добавление http://
- docker/searxng-config: настройки для JSON API SearxNG

Co-authored-by: Cursor <cursoragent@cursor.com>

apps/chat-service/src/lib/agents/media/image.ts

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+/* I don't think can be classified as agents but to keep the structure consistent i guess ill keep it here */
+
+import { searchSearxng } from '@/lib/searxng';
+import {
+  imageSearchFewShots,
+  imageSearchPrompt,
+} from '@/lib/prompts/media/image';
+import BaseLLM from '@/lib/models/base/llm';
+import z from 'zod';
+import { ChatTurnMessage } from '@/lib/types';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+
+type ImageSearchChainInput = {
+  chatHistory: ChatTurnMessage[];
+  query: string;
+};
+
+type ImageSearchResult = {
+  img_src: string;
+  url: string;
+  title: string;
+};
+
+const searchImages = async (
+  input: ImageSearchChainInput,
+  llm: BaseLLM<any>,
+) => {
+  const schema = z.object({
+    query: z.string().describe('The image search query.'),
+  });
+
+  const res = await llm.generateObject<typeof schema>({
+    messages: [
+      {
+        role: 'system',
+        content: imageSearchPrompt,
+      },
+      ...imageSearchFewShots,
+      {
+        role: 'user',
+        content: `<conversation>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation>\n<follow_up>\n${input.query}\n</follow_up>`,
+      },
+    ],
+    schema: schema,
+  });
+
+  const searchRes = await searchSearxng(res.query, {
+    engines: ['bing images', 'google images'],
+  });
+
+  const images: ImageSearchResult[] = [];
+
+  searchRes.results.forEach((result) => {
+    if (result.img_src && result.url && result.title) {
+      images.push({
+        img_src: result.img_src,
+        url: result.url,
+        title: result.title,
+      });
+    }
+  });
+
+  return images.slice(0, 10);
+};
+
+export default searchImages;

apps/chat-service/src/lib/agents/media/video.ts

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+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+import { searchSearxng } from '@/lib/searxng';
+import {
+  videoSearchFewShots,
+  videoSearchPrompt,
+} from '@/lib/prompts/media/videos';
+import { ChatTurnMessage } from '@/lib/types';
+import BaseLLM from '@/lib/models/base/llm';
+import z from 'zod';
+
+type VideoSearchChainInput = {
+  chatHistory: ChatTurnMessage[];
+  query: string;
+};
+
+type VideoSearchResult = {
+  img_src: string;
+  url: string;
+  title: string;
+  iframe_src: string;
+};
+
+const searchVideos = async (
+  input: VideoSearchChainInput,
+  llm: BaseLLM<any>,
+) => {
+  const schema = z.object({
+    query: z.string().describe('The video search query.'),
+  });
+
+  const res = await llm.generateObject<typeof schema>({
+    messages: [
+      {
+        role: 'system',
+        content: videoSearchPrompt,
+      },
+      ...videoSearchFewShots,
+      {
+        role: 'user',
+        content: `<conversation>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation>\n<follow_up>\n${input.query}\n</follow_up>`,
+      },
+    ],
+    schema: schema,
+  });
+
+  const searchRes = await searchSearxng(res.query, {
+    engines: ['youtube'],
+  });
+
+  const videos: VideoSearchResult[] = [];
+
+  searchRes.results.forEach((result) => {
+    if (result.thumbnail && result.url && result.title && result.iframe_src) {
+      videos.push({
+        img_src: result.thumbnail,
+        url: result.url,
+        title: result.title,
+        iframe_src: result.iframe_src,
+      });
+    }
+  });
+
+  return videos.slice(0, 10);
+};
+
+export default searchVideos;

apps/chat-service/src/lib/agents/search/api.ts

@@ -0,0 +1,99 @@
+import { ResearcherOutput, SearchAgentInput } from './types';
+import SessionManager from '@/lib/session';
+import { classify } from './classifier';
+import Researcher from './researcher';
+import { getWriterPrompt } from '@/lib/prompts/search/writer';
+import { WidgetExecutor } from './widgets';
+
+class APISearchAgent {
+  async searchAsync(session: SessionManager, input: SearchAgentInput) {
+    const classification = await classify({
+      chatHistory: input.chatHistory,
+      enabledSources: input.config.sources,
+      query: input.followUp,
+      llm: input.config.llm,
+    });
+
+    const widgetPromise = WidgetExecutor.executeAll({
+      classification,
+      chatHistory: input.chatHistory,
+      followUp: input.followUp,
+      llm: input.config.llm,
+    });
+
+    let searchPromise: Promise<ResearcherOutput> | null = null;
+
+    if (!classification.classification.skipSearch) {
+      const researcher = new Researcher();
+      searchPromise = researcher.research(SessionManager.createSession(), {
+        chatHistory: input.chatHistory,
+        followUp: input.followUp,
+        classification: classification,
+        config: input.config,
+      });
+    }
+
+    const [widgetOutputs, searchResults] = await Promise.all([
+      widgetPromise,
+      searchPromise,
+    ]);
+
+    if (searchResults) {
+      session.emit('data', {
+        type: 'searchResults',
+        data: searchResults.searchFindings,
+      });
+    }
+
+    session.emit('data', {
+      type: 'researchComplete',
+    });
+
+    const finalContext =
+      searchResults?.searchFindings
+        .map(
+          (f, index) =>
+            `<result index=${index + 1} title=${f.metadata.title}>${f.content}</result>`,
+        )
+        .join('\n') || '';
+
+    const widgetContext = widgetOutputs
+      .map((o) => {
+        return `<result>${o.llmContext}</result>`;
+      })
+      .join('\n-------------\n');
+
+    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>`;
+
+    const writerPrompt = getWriterPrompt(
+      finalContextWithWidgets,
+      input.config.systemInstructions,
+      input.config.mode,
+    );
+
+    const answerStream = input.config.llm.streamText({
+      messages: [
+        {
+          role: 'system',
+          content: writerPrompt,
+        },
+        ...input.chatHistory,
+        {
+          role: 'user',
+          content: input.followUp,
+        },
+      ],
+    });
+
+    for await (const chunk of answerStream) {
+      session.emit('data', {
+        type: 'response',
+        data: chunk.contentChunk,
+      });
+    }
+
+    session.emit('end', {});
+  }
+}
+
+export default APISearchAgent;

apps/chat-service/src/lib/agents/search/classifier.ts

@@ -0,0 +1,53 @@
+import z from 'zod';
+import { ClassifierInput } from './types';
+import { classifierPrompt } from '@/lib/prompts/search/classifier';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+
+const schema = z.object({
+  classification: z.object({
+    skipSearch: z
+      .boolean()
+      .describe('Indicates whether to skip the search step.'),
+    personalSearch: z
+      .boolean()
+      .describe('Indicates whether to perform a personal search.'),
+    academicSearch: z
+      .boolean()
+      .describe('Indicates whether to perform an academic search.'),
+    discussionSearch: z
+      .boolean()
+      .describe('Indicates whether to perform a discussion search.'),
+    showWeatherWidget: z
+      .boolean()
+      .describe('Indicates whether to show the weather widget.'),
+    showStockWidget: z
+      .boolean()
+      .describe('Indicates whether to show the stock widget.'),
+    showCalculationWidget: z
+      .boolean()
+      .describe('Indicates whether to show the calculation widget.'),
+  }),
+  standaloneFollowUp: z
+    .string()
+    .describe(
+      "A self-contained, context-independent reformulation of the user's question.",
+    ),
+});
+
+export const classify = async (input: ClassifierInput) => {
+  const output = await input.llm.generateObject<typeof schema>({
+    messages: [
+      {
+        role: 'system',
+        content: classifierPrompt,
+      },
+      {
+        role: 'user',
+        content: `<conversation_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation_history>\n<user_query>\n${input.query}\n</user_query>`,
+      },
+    ],
+    schema,
+  });
+
+  return output;
+};

apps/chat-service/src/lib/agents/search/index.ts

@@ -0,0 +1,186 @@
+import { ResearcherOutput, SearchAgentInput } from './types';
+import SessionManager from '@/lib/session';
+import { classify } from './classifier';
+import Researcher from './researcher';
+import { getWriterPrompt } from '@/lib/prompts/search/writer';
+import { WidgetExecutor } from './widgets';
+import db from '@/lib/db';
+import { chats, messages } from '@/lib/db/schema';
+import { and, eq, gt } from 'drizzle-orm';
+import { TextBlock } from '@/lib/types';
+
+class SearchAgent {
+  async searchAsync(session: SessionManager, input: SearchAgentInput) {
+    const exists = await db.query.messages.findFirst({
+      where: and(
+        eq(messages.chatId, input.chatId),
+        eq(messages.messageId, input.messageId),
+      ),
+    });
+
+    if (!exists) {
+      await db.insert(messages).values({
+        chatId: input.chatId,
+        messageId: input.messageId,
+        backendId: session.id,
+        query: input.followUp,
+        createdAt: new Date().toISOString(),
+        status: 'answering',
+        responseBlocks: [],
+      });
+    } else {
+      await db
+        .delete(messages)
+        .where(
+          and(eq(messages.chatId, input.chatId), gt(messages.id, exists.id)),
+        )
+        .execute();
+      await db
+        .update(messages)
+        .set({
+          status: 'answering',
+          backendId: session.id,
+          responseBlocks: [],
+        })
+        .where(
+          and(
+            eq(messages.chatId, input.chatId),
+            eq(messages.messageId, input.messageId),
+          ),
+        )
+        .execute();
+    }
+
+    const classification = await classify({
+      chatHistory: input.chatHistory,
+      enabledSources: input.config.sources,
+      query: input.followUp,
+      llm: input.config.llm,
+    });
+
+    const widgetPromise = WidgetExecutor.executeAll({
+      classification,
+      chatHistory: input.chatHistory,
+      followUp: input.followUp,
+      llm: input.config.llm,
+    }).then((widgetOutputs) => {
+      widgetOutputs.forEach((o) => {
+        session.emitBlock({
+          id: crypto.randomUUID(),
+          type: 'widget',
+          data: {
+            widgetType: o.type,
+            params: o.data,
+          },
+        });
+      });
+      return widgetOutputs;
+    });
+
+    let searchPromise: Promise<ResearcherOutput> | null = null;
+
+    if (!classification.classification.skipSearch) {
+      const researcher = new Researcher();
+      searchPromise = researcher.research(session, {
+        chatHistory: input.chatHistory,
+        followUp: input.followUp,
+        classification: classification,
+        config: input.config,
+      });
+    }
+
+    const [widgetOutputs, searchResults] = await Promise.all([
+      widgetPromise,
+      searchPromise,
+    ]);
+
+    session.emit('data', {
+      type: 'researchComplete',
+    });
+
+    const finalContext =
+      searchResults?.searchFindings
+        .map(
+          (f, index) =>
+            `<result index=${index + 1} title=${f.metadata.title}>${f.content}</result>`,
+        )
+        .join('\n') || '';
+
+    const widgetContext = widgetOutputs
+      .map((o) => {
+        return `<result>${o.llmContext}</result>`;
+      })
+      .join('\n-------------\n');
+
+    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>`;
+
+    const writerPrompt = getWriterPrompt(
+      finalContextWithWidgets,
+      input.config.systemInstructions,
+      input.config.mode,
+    );
+    const answerStream = input.config.llm.streamText({
+      messages: [
+        {
+          role: 'system',
+          content: writerPrompt,
+        },
+        ...input.chatHistory,
+        {
+          role: 'user',
+          content: input.followUp,
+        },
+      ],
+    });
+
+    let responseBlockId = '';
+
+    for await (const chunk of answerStream) {
+      if (!responseBlockId) {
+        const block: TextBlock = {
+          id: crypto.randomUUID(),
+          type: 'text',
+          data: chunk.contentChunk,
+        };
+
+        session.emitBlock(block);
+
+        responseBlockId = block.id;
+      } else {
+        const block = session.getBlock(responseBlockId) as TextBlock | null;
+
+        if (!block) {
+          continue;
+        }
+
+        block.data += chunk.contentChunk;
+
+        session.updateBlock(block.id, [
+          {
+            op: 'replace',
+            path: '/data',
+            value: block.data,
+          },
+        ]);
+      }
+    }
+
+    session.emit('end', {});
+
+    await db
+      .update(messages)
+      .set({
+        status: 'completed',
+        responseBlocks: session.getAllBlocks(),
+      })
+      .where(
+        and(
+          eq(messages.chatId, input.chatId),
+          eq(messages.messageId, input.messageId),
+        ),
+      )
+      .execute();
+  }
+}
+
+export default SearchAgent;

apps/chat-service/src/lib/agents/search/types.ts

@@ -0,0 +1,122 @@
+import z from 'zod';
+import BaseLLM from '../../models/base/llm';
+import BaseEmbedding from '@/lib/models/base/embedding';
+import SessionManager from '@/lib/session';
+import { ChatTurnMessage, Chunk } from '@/lib/types';
+
+export type SearchSources = 'web' | 'discussions' | 'academic';
+
+export type SearchAgentConfig = {
+  sources: SearchSources[];
+  fileIds: string[];
+  llm: BaseLLM<any>;
+  embedding: BaseEmbedding<any>;
+  mode: 'speed' | 'balanced' | 'quality';
+  systemInstructions: string;
+};
+
+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[];
+};
+
+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>;
+  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[];
+  }) => boolean;
+  execute: (
+    params: z.infer<TSchema>,
+    additionalConfig: AdditionalConfig & {
+      researchBlockId: string;
+      fileIds: string[];
+    },
+  ) => Promise<ActionOutput>;
+}

apps/chat-service/src/lib/agents/search/widgets/calculationWidget.ts

@@ -0,0 +1,71 @@
+import z from 'zod';
+import { Widget } from '../types';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+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;

apps/chat-service/src/lib/agents/search/widgets/executor.ts

@@ -0,0 +1,36 @@
+import { Widget, WidgetInput, WidgetOutput } from '../types';
+
+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;

apps/chat-service/src/lib/agents/search/widgets/index.ts

@@ -0,0 +1,10 @@
+import calculationWidget from './calculationWidget';
+import WidgetExecutor from './executor';
+import weatherWidget from './weatherWidget';
+import stockWidget from './stockWidget';
+
+WidgetExecutor.register(weatherWidget);
+WidgetExecutor.register(calculationWidget);
+WidgetExecutor.register(stockWidget);
+
+export { WidgetExecutor };

apps/chat-service/src/lib/agents/search/widgets/stockWidget.ts

@@ -0,0 +1,434 @@
+import z from 'zod';
+import { Widget } from '../types';
+import YahooFinance from 'yahoo-finance2';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+
+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;

apps/chat-service/src/lib/agents/search/widgets/weatherWidget.ts

@@ -0,0 +1,203 @@
+import z from 'zod';
+import { Widget } from '../types';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+
+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}&current=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=${params.lon}&current=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
+            {
+              headers: {
+                'User-Agent': 'GooSeek',
+                'Content-Type': 'application/json',
+              },
+            },
+          ),
+          fetch(
+            `https://nominatim.openstreetmap.org/reverse?lat=${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;

apps/chat-service/src/lib/agents/suggestions/index.ts

@@ -0,0 +1,38 @@
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+import { suggestionGeneratorPrompt } from '@/lib/prompts/suggestions';
+import { ChatTurnMessage } from '@/lib/types';
+import z from 'zod';
+import BaseLLM from '@/lib/models/base/llm';
+
+type SuggestionGeneratorInput = {
+  chatHistory: ChatTurnMessage[];
+};
+
+const schema = z.object({
+  suggestions: z
+    .array(z.string())
+    .describe('List of suggested questions or prompts'),
+});
+
+const generateSuggestions = async (
+  input: SuggestionGeneratorInput,
+  llm: BaseLLM<any>,
+) => {
+  const res = await llm.generateObject<typeof schema>({
+    messages: [
+      {
+        role: 'system',
+        content: suggestionGeneratorPrompt,
+      },
+      {
+        role: 'user',
+        content: `<chat_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</chat_history>`,
+      },
+    ],
+    schema,
+  });
+
+  return res.suggestions;
+};
+
+export default generateSuggestions;