feat(app): handle new architecture

drizzle/0002_daffy_wrecker.sql

@@ -0,0 +1,15 @@
+PRAGMA foreign_keys=OFF;--> statement-breakpoint
+CREATE TABLE `__new_messages` (
+	`id` integer PRIMARY KEY NOT NULL,
+	`messageId` text NOT NULL,
+	`chatId` text NOT NULL,
+	`backendId` text NOT NULL,
+	`query` text NOT NULL,
+	`createdAt` text NOT NULL,
+	`responseBlocks` text DEFAULT '[]',
+	`status` text DEFAULT 'answering'
+);
+--> statement-breakpoint
+DROP TABLE `messages`;--> statement-breakpoint
+ALTER TABLE `__new_messages` RENAME TO `messages`;--> statement-breakpoint
+PRAGMA foreign_keys=ON;

drizzle/meta/0002_snapshot.json

@@ -0,0 +1,132 @@
+{
+  "version": "6",
+  "dialect": "sqlite",
+  "id": "1c5eb804-d6b4-48ec-9a8f-75fb729c8e52",
+  "prevId": "6dedf55f-0e44-478f-82cf-14a21ac686f8",
+  "tables": {
+    "chats": {
+      "name": "chats",
+      "columns": {
+        "id": {
+          "name": "id",
+          "type": "text",
+          "primaryKey": true,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "title": {
+          "name": "title",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "createdAt": {
+          "name": "createdAt",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "focusMode": {
+          "name": "focusMode",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "files": {
+          "name": "files",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": false,
+          "autoincrement": false,
+          "default": "'[]'"
+        }
+      },
+      "indexes": {},
+      "foreignKeys": {},
+      "compositePrimaryKeys": {},
+      "uniqueConstraints": {},
+      "checkConstraints": {}
+    },
+    "messages": {
+      "name": "messages",
+      "columns": {
+        "id": {
+          "name": "id",
+          "type": "integer",
+          "primaryKey": true,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "messageId": {
+          "name": "messageId",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "chatId": {
+          "name": "chatId",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "backendId": {
+          "name": "backendId",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "query": {
+          "name": "query",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "createdAt": {
+          "name": "createdAt",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": true,
+          "autoincrement": false
+        },
+        "responseBlocks": {
+          "name": "responseBlocks",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": false,
+          "autoincrement": false,
+          "default": "'[]'"
+        },
+        "status": {
+          "name": "status",
+          "type": "text",
+          "primaryKey": false,
+          "notNull": false,
+          "autoincrement": false,
+          "default": "'answering'"
+        }
+      },
+      "indexes": {},
+      "foreignKeys": {},
+      "compositePrimaryKeys": {},
+      "uniqueConstraints": {},
+      "checkConstraints": {}
+    }
+  },
+  "views": {},
+  "enums": {},
+  "_meta": {
+    "schemas": {},
+    "tables": {},
+    "columns": {}
+  },
+  "internal": {
+    "indexes": {}
+  }
+}

drizzle/meta/_journal.json

@@ -15,6 +15,13 @@
       "when": 1758863991284,
       "tag": "0001_wise_rockslide",
       "breakpoints": true
+    },
+    {
+      "idx": 2,
+      "version": "6",
+      "when": 1763732708332,
+      "tag": "0002_daffy_wrecker",
+      "breakpoints": true
     }
   ]
 }

package.json

@@ -35,19 +35,26 @@
     "html-to-text": "^9.0.5",
     "jspdf": "^3.0.1",
     "langchain": "^1.0.4",
+    "lightweight-charts": "^5.0.9",
     "lucide-react": "^0.363.0",
     "mammoth": "^1.9.1",
     "markdown-to-jsx": "^7.7.2",
+    "mathjs": "^15.1.0",
     "next": "^15.2.2",
     "next-themes": "^0.3.0",
+    "ollama": "^0.6.3",
+    "openai": "^6.9.0",
+    "partial-json": "^0.1.7",
     "pdf-parse": "^1.1.1",
     "react": "^18",
     "react-dom": "^18",
     "react-text-to-speech": "^0.14.5",
     "react-textarea-autosize": "^8.5.3",
+    "rfc6902": "^5.1.2",
     "sonner": "^1.4.41",
     "tailwind-merge": "^2.2.2",
     "winston": "^3.17.0",
+    "yahoo-finance2": "^3.10.2",
     "yet-another-react-lightbox": "^3.17.2",
     "zod": "^4.1.12"
   },

src/app/api/chat/route.ts

@@ -1,14 +1,10 @@
 import crypto from 'crypto';
-import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
-import { EventEmitter } from 'stream';
-import db from '@/lib/db';
-import { chats, messages as messagesSchema } from '@/lib/db/schema';
-import { and, eq, gt } from 'drizzle-orm';
-import { getFileDetails } from '@/lib/utils/files';
-import { searchHandlers } from '@/lib/search';
 import { z } from 'zod';
 import ModelRegistry from '@/lib/models/registry';
 import { ModelWithProvider } from '@/lib/models/types';
+import SearchAgent from '@/lib/agents/search';
+import SessionManager from '@/lib/session';
+import { ChatTurnMessage } from '@/lib/types';
 
 export const runtime = 'nodejs';
 export const dynamic = 'force-dynamic';
@@ -20,47 +16,25 @@ const messageSchema = z.object({
 });
 
 const chatModelSchema: z.ZodType<ModelWithProvider> = z.object({
-  providerId: z.string({
-    errorMap: () => ({
-      message: 'Chat model provider id must be provided',
-    }),
-  }),
-  key: z.string({
-    errorMap: () => ({
-      message: 'Chat model key must be provided',
-    }),
-  }),
+  providerId: z.string({ message: 'Chat model provider id must be provided' }),
+  key: z.string({ message: 'Chat model key must be provided' }),
 });
 
 const embeddingModelSchema: z.ZodType<ModelWithProvider> = z.object({
   providerId: z.string({
-    errorMap: () => ({
-      message: 'Embedding model provider id must be provided',
-    }),
-  }),
-  key: z.string({
-    errorMap: () => ({
-      message: 'Embedding model key must be provided',
-    }),
+    message: 'Embedding model provider id must be provided',
   }),
+  key: z.string({ message: 'Embedding model key must be provided' }),
 });
 
 const bodySchema = z.object({
   message: messageSchema,
   optimizationMode: z.enum(['speed', 'balanced', 'quality'], {
-    errorMap: () => ({
-      message: 'Optimization mode must be one of: speed, balanced, quality',
-    }),
+    message: 'Optimization mode must be one of: speed, balanced, quality',
   }),
   focusMode: z.string().min(1, 'Focus mode is required'),
   history: z
-    .array(
-      z.tuple([z.string(), z.string()], {
-        errorMap: () => ({
-          message: 'History items must be tuples of two strings',
-        }),
-      }),
-    )
+    .array(z.tuple([z.string(), z.string()]))
     .optional()
     .default([]),
   files: z.array(z.string()).optional().default([]),
@@ -78,7 +52,7 @@ const safeValidateBody = (data: unknown) => {
   if (!result.success) {
     return {
       success: false,
-      error: result.error.errors.map((e) => ({
+      error: result.error.issues.map((e: any) => ({
         path: e.path.join('.'),
         message: e.message,
       })),
@@ -91,151 +65,12 @@ const safeValidateBody = (data: unknown) => {
   };
 };
 
-const handleEmitterEvents = async (
-  stream: EventEmitter,
-  writer: WritableStreamDefaultWriter,
-  encoder: TextEncoder,
-  chatId: string,
-) => {
-  let receivedMessage = '';
-  const aiMessageId = crypto.randomBytes(7).toString('hex');
-
-  stream.on('data', (data) => {
-    const parsedData = JSON.parse(data);
-    if (parsedData.type === 'response') {
-      writer.write(
-        encoder.encode(
-          JSON.stringify({
-            type: 'message',
-            data: parsedData.data,
-            messageId: aiMessageId,
-          }) + '\n',
-        ),
-      );
-
-      receivedMessage += parsedData.data;
-    } else if (parsedData.type === 'sources') {
-      writer.write(
-        encoder.encode(
-          JSON.stringify({
-            type: 'sources',
-            data: parsedData.data,
-            messageId: aiMessageId,
-          }) + '\n',
-        ),
-      );
-
-      const sourceMessageId = crypto.randomBytes(7).toString('hex');
-
-      db.insert(messagesSchema)
-        .values({
-          chatId: chatId,
-          messageId: sourceMessageId,
-          role: 'source',
-          sources: parsedData.data,
-          createdAt: new Date().toString(),
-        })
-        .execute();
-    }
-  });
-  stream.on('end', () => {
-    writer.write(
-      encoder.encode(
-        JSON.stringify({
-          type: 'messageEnd',
-        }) + '\n',
-      ),
-    );
-    writer.close();
-
-    db.insert(messagesSchema)
-      .values({
-        content: receivedMessage,
-        chatId: chatId,
-        messageId: aiMessageId,
-        role: 'assistant',
-        createdAt: new Date().toString(),
-      })
-      .execute();
-  });
-  stream.on('error', (data) => {
-    const parsedData = JSON.parse(data);
-    writer.write(
-      encoder.encode(
-        JSON.stringify({
-          type: 'error',
-          data: parsedData.data,
-        }),
-      ),
-    );
-    writer.close();
-  });
-};
-
-const handleHistorySave = async (
-  message: Message,
-  humanMessageId: string,
-  focusMode: string,
-  files: string[],
-) => {
-  const chat = await db.query.chats.findFirst({
-    where: eq(chats.id, message.chatId),
-  });
-
-  const fileData = files.map(getFileDetails);
-
-  if (!chat) {
-    await db
-      .insert(chats)
-      .values({
-        id: message.chatId,
-        title: message.content,
-        createdAt: new Date().toString(),
-        focusMode: focusMode,
-        files: fileData,
-      })
-      .execute();
-  } else if (JSON.stringify(chat.files ?? []) != JSON.stringify(fileData)) {
-    db.update(chats)
-      .set({
-        files: files.map(getFileDetails),
-      })
-      .where(eq(chats.id, message.chatId));
-  }
-
-  const messageExists = await db.query.messages.findFirst({
-    where: eq(messagesSchema.messageId, humanMessageId),
-  });
-
-  if (!messageExists) {
-    await db
-      .insert(messagesSchema)
-      .values({
-        content: message.content,
-        chatId: message.chatId,
-        messageId: humanMessageId,
-        role: 'user',
-        createdAt: new Date().toString(),
-      })
-      .execute();
-  } else {
-    await db
-      .delete(messagesSchema)
-      .where(
-        and(
-          gt(messagesSchema.id, messageExists.id),
-          eq(messagesSchema.chatId, message.chatId),
-        ),
-      )
-      .execute();
-  }
-};
-
 export const POST = async (req: Request) => {
   try {
     const reqBody = (await req.json()) as Body;
 
     const parseBody = safeValidateBody(reqBody);
+
     if (!parseBody.success) {
       return Response.json(
         { message: 'Invalid request body', error: parseBody.error },
@@ -265,48 +100,116 @@ export const POST = async (req: Request) => {
       ),
     ]);
 
-    const humanMessageId =
-      message.messageId ?? crypto.randomBytes(7).toString('hex');
-
-    const history: BaseMessage[] = body.history.map((msg) => {
+    const history: ChatTurnMessage[] = body.history.map((msg) => {
       if (msg[0] === 'human') {
-        return new HumanMessage({
+        return {
+          role: 'user',
           content: msg[1],
-        });
+        };
       } else {
-        return new AIMessage({
+        return {
+          role: 'assistant',
           content: msg[1],
-        });
+        };
       }
     });
 
-    const handler = searchHandlers[body.focusMode];
-
-    if (!handler) {
-      return Response.json(
-        {
-          message: 'Invalid focus mode',
-        },
-        { status: 400 },
-      );
-    }
-
-    const stream = await handler.searchAndAnswer(
-      message.content,
-      history,
-      llm,
-      embedding,
-      body.optimizationMode,
-      body.files,
-      body.systemInstructions as string,
-    );
+    const agent = new SearchAgent();
+    const session = SessionManager.createSession();
 
     const responseStream = new TransformStream();
     const writer = responseStream.writable.getWriter();
     const encoder = new TextEncoder();
 
-    handleEmitterEvents(stream, writer, encoder, message.chatId);
-    handleHistorySave(message, humanMessageId, body.focusMode, body.files);
+    let receivedMessage = '';
+
+    session.addListener('data', (data: any) => {
+      if (data.type === 'response') {
+        writer.write(
+          encoder.encode(
+            JSON.stringify({
+              type: 'message',
+              data: data.data,
+            }) + '\n',
+          ),
+        );
+        receivedMessage += data.data;
+      } else if (data.type === 'sources') {
+        writer.write(
+          encoder.encode(
+            JSON.stringify({
+              type: 'sources',
+              data: data.data,
+            }) + '\n',
+          ),
+        );
+      } else if (data.type === 'block') {
+        writer.write(
+          encoder.encode(
+            JSON.stringify({
+              type: 'block',
+              block: data.block,
+            }) + '\n',
+          ),
+        );
+      } else if (data.type === 'updateBlock') {
+        writer.write(
+          encoder.encode(
+            JSON.stringify({
+              type: 'updateBlock',
+              blockId: data.blockId,
+              patch: data.patch,
+            }) + '\n',
+          ),
+        );
+      } else if (data.type === 'researchComplete') {
+        writer.write(
+          encoder.encode(
+            JSON.stringify({
+              type: 'researchComplete',
+            }) + '\n',
+          ),
+        );
+      }
+    });
+
+    session.addListener('end', () => {
+      writer.write(
+        encoder.encode(
+          JSON.stringify({
+            type: 'messageEnd',
+          }) + '\n',
+        ),
+      );
+      writer.close();
+      session.removeAllListeners();
+    });
+
+    session.addListener('error', (data: any) => {
+      writer.write(
+        encoder.encode(
+          JSON.stringify({
+            type: 'error',
+            data: data.data,
+          }) + '\n',
+        ),
+      );
+      writer.close();
+      session.removeAllListeners();
+    });
+
+    agent.searchAsync(session, {
+      chatHistory: history,
+      followUp: message.content,
+      config: {
+        llm,
+        embedding: embedding,
+        sources: ['web'],
+        mode: body.optimizationMode,
+      },
+    });
+
+    /*  handleHistorySave(message, humanMessageId, body.focusMode, body.files); */
 
     return new Response(responseStream.readable, {
       headers: {

src/app/api/images/route.ts

@@ -1,7 +1,6 @@
 import searchImages from '@/lib/agents/media/image';
 import ModelRegistry from '@/lib/models/registry';
 import { ModelWithProvider } from '@/lib/models/types';
-import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
 
 interface ImageSearchBody {
   query: string;
@@ -20,19 +19,9 @@ export const POST = async (req: Request) => {
       body.chatModel.key,
     );
 
-    const chatHistory = body.chatHistory
-      .map((msg: any) => {
-        if (msg.role === 'user') {
-          return new HumanMessage(msg.content);
-        } else if (msg.role === 'assistant') {
-          return new AIMessage(msg.content);
-        }
-      })
-      .filter((msg) => msg !== undefined) as BaseMessage[];
-
     const images = await searchImages(
       {
-        chatHistory: chatHistory,
+        chatHistory: body.chatHistory,
         query: body.query,
       },
       llm,

src/app/api/search/route.ts

@@ -1,8 +1,8 @@
-import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
-import { MetaSearchAgentType } from '@/lib/search/metaSearchAgent';
-import { searchHandlers } from '@/lib/search';
 import ModelRegistry from '@/lib/models/registry';
 import { ModelWithProvider } from '@/lib/models/types';
+import SessionManager from '@/lib/session';
+import SearchAgent from '@/lib/agents/search';
+import { ChatTurnMessage } from '@/lib/types';
 
 interface ChatRequestBody {
   optimizationMode: 'speed' | 'balanced';
@@ -40,27 +40,26 @@ export const POST = async (req: Request) => {
       ),
     ]);
 
-    const history: BaseMessage[] = body.history.map((msg) => {
+    const history: ChatTurnMessage[] = body.history.map((msg) => {
       return msg[0] === 'human'
-        ? new HumanMessage({ content: msg[1] })
-        : new AIMessage({ content: msg[1] });
+        ? { role: 'user', content: msg[1] }
+        : { role: 'assistant', content: msg[1] };
     });
 
-    const searchHandler: MetaSearchAgentType = searchHandlers[body.focusMode];
+    const session = SessionManager.createSession();
 
-    if (!searchHandler) {
-      return Response.json({ message: 'Invalid focus mode' }, { status: 400 });
-    }
+    const agent = new SearchAgent();
 
-    const emitter = await searchHandler.searchAndAnswer(
-      body.query,
-      history,
-      llm,
-      embeddings,
-      body.optimizationMode,
-      [],
-      body.systemInstructions || '',
-    );
+    agent.searchAsync(session, {
+      chatHistory: history,
+      config: {
+        embedding: embeddings,
+        llm: llm,
+        sources: ['web', 'discussions', 'academic'],
+        mode: 'balanced',
+      },
+      followUp: body.query,
+    });
 
     if (!body.stream) {
       return new Promise(
@@ -71,7 +70,7 @@ export const POST = async (req: Request) => {
           let message = '';
           let sources: any[] = [];
 
-          emitter.on('data', (data: string) => {
+          session.addListener('data', (data: string) => {
             try {
               const parsedData = JSON.parse(data);
               if (parsedData.type === 'response') {
@@ -89,11 +88,11 @@ export const POST = async (req: Request) => {
             }
           });
 
-          emitter.on('end', () => {
+          session.addListener('end', () => {
             resolve(Response.json({ message, sources }, { status: 200 }));
           });
 
-          emitter.on('error', (error: any) => {
+          session.addListener('error', (error: any) => {
             reject(
               Response.json(
                 { message: 'Search error', error },
@@ -124,14 +123,14 @@ export const POST = async (req: Request) => {
         );
 
         signal.addEventListener('abort', () => {
-          emitter.removeAllListeners();
+          session.removeAllListeners();
 
           try {
             controller.close();
-          } catch (error) { }
+          } catch (error) {}
         });
 
-        emitter.on('data', (data: string) => {
+        session.addListener('data', (data: string) => {
           if (signal.aborted) return;
 
           try {
@@ -162,7 +161,7 @@ export const POST = async (req: Request) => {
           }
         });
 
-        emitter.on('end', () => {
+        session.addListener('end', () => {
           if (signal.aborted) return;
 
           controller.enqueue(
@@ -175,7 +174,7 @@ export const POST = async (req: Request) => {
           controller.close();
         });
 
-        emitter.on('error', (error: any) => {
+        session.addListener('error', (error: any) => {
           if (signal.aborted) return;
 
           controller.error(error);

src/app/api/suggestions/route.ts

@@ -19,19 +19,9 @@ export const POST = async (req: Request) => {
       body.chatModel.key,
     );
 
-    const chatHistory = body.chatHistory
-      .map((msg: any) => {
-        if (msg.role === 'user') {
-          return new HumanMessage(msg.content);
-        } else if (msg.role === 'assistant') {
-          return new AIMessage(msg.content);
-        }
-      })
-      .filter((msg) => msg !== undefined) as BaseMessage[];
-
     const suggestions = await generateSuggestions(
       {
-        chatHistory,
+        chatHistory: body.chatHistory,
       },
       llm,
     );

src/app/api/uploads/route.ts

@@ -7,6 +7,7 @@ import { DocxLoader } from '@langchain/community/document_loaders/fs/docx';
 import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
 import { Document } from '@langchain/core/documents';
 import ModelRegistry from '@/lib/models/registry';
+import { Chunk } from '@/lib/types';
 
 interface FileRes {
   fileName: string;
@@ -87,9 +88,17 @@ export async function POST(req: Request) {
           }),
         );
 
-        const embeddings = await model.embedDocuments(
-          splitted.map((doc) => doc.pageContent),
+        const chunks: Chunk[] = splitted.map((doc) => {
+          return {
+            content: doc.pageContent,
+            metadata: doc.metadata,
+          }
+        });
+
+        const embeddings = await model.embedChunks(
+          chunks
         );
+        
         const embeddingsDataPath = filePath.replace(
           /\.\w+$/,
           '-embeddings.json',

src/app/api/videos/route.ts

@@ -1,7 +1,6 @@
 import handleVideoSearch from '@/lib/agents/media/video';
 import ModelRegistry from '@/lib/models/registry';
 import { ModelWithProvider } from '@/lib/models/types';
-import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
 
 interface VideoSearchBody {
   query: string;
@@ -20,19 +19,9 @@ export const POST = async (req: Request) => {
       body.chatModel.key,
     );
 
-    const chatHistory = body.chatHistory
-      .map((msg: any) => {
-        if (msg.role === 'user') {
-          return new HumanMessage(msg.content);
-        } else if (msg.role === 'assistant') {
-          return new AIMessage(msg.content);
-        }
-      })
-      .filter((msg) => msg !== undefined) as BaseMessage[];
-
     const videos = await handleVideoSearch(
       {
-        chatHistory: chatHistory,
+        chatHistory: body.chatHistory,
         query: body.query,
       },
       llm,

src/components/AssistantSteps.tsx

@@ -0,0 +1,197 @@
+'use client';
+
+import { Brain, Search, FileText, ChevronDown, ChevronUp } from 'lucide-react';
+import { motion, AnimatePresence } from 'framer-motion';
+import { useEffect, useState } from 'react';
+import { ResearchBlock, ResearchBlockSubStep } from '@/lib/types';
+import { useChat } from '@/lib/hooks/useChat';
+
+const getStepIcon = (step: ResearchBlockSubStep) => {
+  if (step.type === 'reasoning') {
+    return <Brain className="w-4 h-4" />;
+  } else if (step.type === 'searching') {
+    return <Search className="w-4 h-4" />;
+  } else if (step.type === 'reading') {
+    return <FileText className="w-4 h-4" />;
+  }
+  return null;
+};
+
+const getStepTitle = (
+  step: ResearchBlockSubStep,
+  isStreaming: boolean,
+): string => {
+  if (step.type === 'reasoning') {
+    return isStreaming && !step.reasoning ? 'Thinking...' : 'Thinking';
+  } else if (step.type === 'searching') {
+    return `Searching ${step.searching.length} ${step.searching.length === 1 ? 'query' : 'queries'}`;
+  } else if (step.type === 'reading') {
+    return `Found ${step.reading.length} ${step.reading.length === 1 ? 'result' : 'results'}`;
+  }
+  return 'Processing';
+};
+
+const AssistantSteps = ({
+  block,
+  status,
+}: {
+  block: ResearchBlock;
+  status: 'answering' | 'completed' | 'error';
+}) => {
+  const [isExpanded, setIsExpanded] = useState(true);
+  const { researchEnded, loading } = useChat();
+
+  useEffect(() => {
+    if (researchEnded) {
+      setIsExpanded(false);
+    } else if (status === 'answering') {
+      setIsExpanded(true);
+    }
+  }, [researchEnded, status]);
+
+  if (!block || block.data.subSteps.length === 0) return null;
+
+  return (
+    <div className="rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 overflow-hidden">
+      <button
+        onClick={() => setIsExpanded(!isExpanded)}
+        className="w-full flex items-center justify-between p-3 hover:bg-light-200 dark:hover:bg-dark-200 transition duration-200"
+      >
+        <div className="flex items-center gap-2">
+          <Brain className="w-4 h-4 text-black dark:text-white" />
+          <span className="text-sm font-medium text-black dark:text-white">
+            Research Progress ({block.data.subSteps.length}{' '}
+            {block.data.subSteps.length === 1 ? 'step' : 'steps'})
+          </span>
+        </div>
+        {isExpanded ? (
+          <ChevronUp className="w-4 h-4 text-black/70 dark:text-white/70" />
+        ) : (
+          <ChevronDown className="w-4 h-4 text-black/70 dark:text-white/70" />
+        )}
+      </button>
+
+      <AnimatePresence>
+        {isExpanded && (
+          <motion.div
+            initial={{ height: 0, opacity: 0 }}
+            animate={{ height: 'auto', opacity: 1 }}
+            exit={{ height: 0, opacity: 0 }}
+            transition={{ duration: 0.2 }}
+            className="border-t border-light-200 dark:border-dark-200"
+          >
+            <div className="p-3 space-y-2">
+              {block.data.subSteps.map((step, index) => {
+                const isLastStep = index === block.data.subSteps.length - 1;
+                const isStreaming = loading && isLastStep && !researchEnded;
+
+                return (
+                  <motion.div
+                    key={step.id}
+                    initial={{ opacity: 0, x: -10 }}
+                    animate={{ opacity: 1, x: 0 }}
+                    transition={{ duration: 0.2, delay: 0 }}
+                    className="flex gap-3"
+                  >
+                    {/* Timeline connector */}
+                    <div className="flex flex-col items-center pt-0.5">
+                      <div
+                        className={`rounded-full p-1.5 bg-light-100 dark:bg-dark-100 text-black/70 dark:text-white/70 ${isStreaming ? 'animate-pulse' : ''}`}
+                      >
+                        {getStepIcon(step)}
+                      </div>
+                      {index < block.data.subSteps.length - 1 && (
+                        <div className="w-0.5 flex-1 min-h-[20px] bg-light-200 dark:bg-dark-200 mt-1.5" />
+                      )}
+                    </div>
+
+                    {/* Step content */}
+                    <div className="flex-1 pb-1">
+                      <span className="text-sm font-medium text-black dark:text-white">
+                        {getStepTitle(step, isStreaming)}
+                      </span>
+
+                      {step.type === 'reasoning' && (
+                        <>
+                          {step.reasoning && (
+                            <p className="text-xs text-black/70 dark:text-white/70 mt-0.5">
+                              {step.reasoning}
+                            </p>
+                          )}
+                          {isStreaming && !step.reasoning && (
+                            <div className="flex items-center gap-1.5 mt-0.5">
+                              <div
+                                className="w-1.5 h-1.5 bg-black/40 dark:bg-white/40 rounded-full animate-bounce"
+                                style={{ animationDelay: '0ms' }}
+                              />
+                              <div
+                                className="w-1.5 h-1.5 bg-black/40 dark:bg-white/40 rounded-full animate-bounce"
+                                style={{ animationDelay: '150ms' }}
+                              />
+                              <div
+                                className="w-1.5 h-1.5 bg-black/40 dark:bg-white/40 rounded-full animate-bounce"
+                                style={{ animationDelay: '300ms' }}
+                              />
+                            </div>
+                          )}
+                        </>
+                      )}
+
+                      {step.type === 'searching' &&
+                        step.searching.length > 0 && (
+                          <div className="flex flex-wrap gap-1.5 mt-1.5">
+                            {step.searching.map((query, idx) => (
+                              <span
+                                key={idx}
+                                className="inline-flex items-center px-2 py-0.5 rounded-md text-xs font-medium bg-light-100 dark:bg-dark-100 text-black/70 dark:text-white/70 border border-light-200 dark:border-dark-200"
+                              >
+                                {query}
+                              </span>
+                            ))}
+                          </div>
+                        )}
+
+                      {step.type === 'reading' && step.reading.length > 0 && (
+                        <div className="flex flex-wrap gap-1.5 mt-1.5">
+                          {step.reading.slice(0, 4).map((result, idx) => {
+                            const url = result.metadata.url || '';
+                            const title = result.metadata.title || 'Untitled';
+                            const domain = url ? new URL(url).hostname : '';
+                            const faviconUrl = domain
+                              ? `https://s2.googleusercontent.com/s2/favicons?domain=${domain}&sz=128`
+                              : '';
+
+                            return (
+                              <span
+                                key={idx}
+                                className="inline-flex items-center gap-1.5 px-2 py-0.5 rounded-md text-xs font-medium bg-light-100 dark:bg-dark-100 text-black/70 dark:text-white/70 border border-light-200 dark:border-dark-200"
+                              >
+                                {faviconUrl && (
+                                  <img
+                                    src={faviconUrl}
+                                    alt=""
+                                    className="w-3 h-3 rounded-sm flex-shrink-0"
+                                    onError={(e) => {
+                                      e.currentTarget.style.display = 'none';
+                                    }}
+                                  />
+                                )}
+                                <span className="line-clamp-1">{title}</span>
+                              </span>
+                            );
+                          })}
+                        </div>
+                      )}
+                    </div>
+                  </motion.div>
+                );
+              })}
+            </div>
+          </motion.div>
+        )}
+      </AnimatePresence>
+    </div>
+  );
+};
+
+export default AssistantSteps;

src/components/Chat.tsx

@@ -7,11 +7,12 @@ import MessageBoxLoading from './MessageBoxLoading';
 import { useChat } from '@/lib/hooks/useChat';
 
 const Chat = () => {
-  const { sections, chatTurns, loading, messageAppeared } = useChat();
+  const { sections, loading, messageAppeared, messages } = useChat();
 
   const [dividerWidth, setDividerWidth] = useState(0);
   const dividerRef = useRef<HTMLDivElement | null>(null);
   const messageEnd = useRef<HTMLDivElement | null>(null);
+  const lastScrolledRef = useRef<number>(0);
 
   useEffect(() => {
     const updateDividerWidth = () => {
@@ -22,35 +23,40 @@ const Chat = () => {
 
     updateDividerWidth();
 
+    const resizeObserver = new ResizeObserver(() => {
+      updateDividerWidth();
+    });
+
+    const currentRef = dividerRef.current;
+    if (currentRef) {
+      resizeObserver.observe(currentRef);
+    }
+
     window.addEventListener('resize', updateDividerWidth);
 
     return () => {
+      if (currentRef) {
+        resizeObserver.unobserve(currentRef);
+      }
+      resizeObserver.disconnect();
       window.removeEventListener('resize', updateDividerWidth);
     };
-  }, []);
+  }, [sections.length]);
 
   useEffect(() => {
     const scroll = () => {
       messageEnd.current?.scrollIntoView({ behavior: 'auto' });
     };
 
-    if (chatTurns.length === 1) {
-      document.title = `${chatTurns[0].content.substring(0, 30)} - Perplexica`;
+    if (messages.length === 1) {
+      document.title = `${messages[0].query.substring(0, 30)} - Perplexica`;
     }
 
-    const messageEndBottom =
-      messageEnd.current?.getBoundingClientRect().bottom ?? 0;
-
-    const distanceFromMessageEnd = window.innerHeight - messageEndBottom;
-
-    if (distanceFromMessageEnd >= -100) {
+    if (sections.length > lastScrolledRef.current) {
       scroll();
+      lastScrolledRef.current = sections.length;
     }
-
-    if (chatTurns[chatTurns.length - 1]?.role === 'user') {
-      scroll();
-    }
-  }, [chatTurns]);
+  }, [messages]);
 
   return (
     <div className="flex flex-col space-y-6 pt-8 pb-44 lg:pb-32 sm:mx-4 md:mx-8">
@@ -58,7 +64,7 @@ const Chat = () => {
         const isLast = i === sections.length - 1;
 
         return (
-          <Fragment key={section.userMessage.messageId}>
+          <Fragment key={section.message.messageId}>
             <MessageBox
               section={section}
               sectionIndex={i}

src/components/ChatWindow.tsx

@@ -1,14 +1,12 @@
 'use client';
 
-import { Document } from '@langchain/core/documents';
 import Navbar from './Navbar';
 import Chat from './Chat';
 import EmptyChat from './EmptyChat';
-import { Settings } from 'lucide-react';
-import Link from 'next/link';
 import NextError from 'next/error';
 import { useChat } from '@/lib/hooks/useChat';
 import SettingsButtonMobile from './Settings/SettingsButtonMobile';
+import { Block, Chunk } from '@/lib/types';
 
 export interface BaseMessage {
   chatId: string;
@@ -16,20 +14,27 @@ export interface BaseMessage {
   createdAt: Date;
 }
 
+export interface Message extends BaseMessage {
+  backendId: string;
+  query: string;
+  responseBlocks: Block[];
+  status: 'answering' | 'completed' | 'error';
+}
+
+export interface UserMessage extends BaseMessage {
+  role: 'user';
+  content: string;
+}
+
 export interface AssistantMessage extends BaseMessage {
   role: 'assistant';
   content: string;
   suggestions?: string[];
 }
 
-export interface UserMessage extends BaseMessage {
-  role: 'user';
-  content: string;
-}
-
 export interface SourceMessage extends BaseMessage {
   role: 'source';
-  sources: Document[];
+  sources: Chunk[];
 }
 
 export interface SuggestionMessage extends BaseMessage {
@@ -37,11 +42,12 @@ export interface SuggestionMessage extends BaseMessage {
   suggestions: string[];
 }
 
-export type Message =
+export type LegacyMessage =
   | AssistantMessage
   | UserMessage
   | SourceMessage
   | SuggestionMessage;
+
 export type ChatTurn = UserMessage | AssistantMessage;
 
 export interface File {
@@ -50,6 +56,11 @@ export interface File {
   fileId: string;
 }
 
+export interface Widget {
+  widgetType: string;
+  params: Record<string, any>;
+}
+
 const ChatWindow = () => {
   const { hasError, notFound, messages } = useChat();
   if (hasError) {

src/components/MessageActions/Copy.tsx

@@ -15,7 +15,14 @@ const Copy = ({
   return (
     <button
       onClick={() => {
-        const contentToCopy = `${initialMessage}${section?.sourceMessage?.sources && section.sourceMessage.sources.length > 0 && `\n\nCitations:\n${section.sourceMessage.sources?.map((source: any, i: any) => `[${i + 1}] ${source.metadata.url}`).join(`\n`)}`}`;
+        const contentToCopy = `${initialMessage}${
+          section?.message.responseBlocks.filter((b) => b.type === 'source')
+            ?.length > 0 &&
+          `\n\nCitations:\n${section.message.responseBlocks
+            .filter((b) => b.type === 'source')
+            ?.map((source: any, i: any) => `[${i + 1}] ${source.metadata.url}`)
+            .join(`\n`)}`
+        }`;
         navigator.clipboard.writeText(contentToCopy);
         setCopied(true);
         setTimeout(() => setCopied(false), 1000);

src/components/MessageBox.tsx

@@ -22,6 +22,9 @@ import { useSpeech } from 'react-text-to-speech';
 import ThinkBox from './ThinkBox';
 import { useChat, Section } from '@/lib/hooks/useChat';
 import Citation from './Citation';
+import AssistantSteps from './AssistantSteps';
+import { ResearchBlock } from '@/lib/types';
+import Renderer from './Widgets/Renderer';
 
 const ThinkTagProcessor = ({
   children,
@@ -46,12 +49,21 @@ const MessageBox = ({
   dividerRef?: MutableRefObject<HTMLDivElement | null>;
   isLast: boolean;
 }) => {
-  const { loading, chatTurns, sendMessage, rewrite } = useChat();
+  const { loading, sendMessage, rewrite, messages, researchEnded } = useChat();
 
-  const parsedMessage = section.parsedAssistantMessage || '';
+  const parsedMessage = section.parsedTextBlocks.join('\n\n');
   const speechMessage = section.speechMessage || '';
   const thinkingEnded = section.thinkingEnded;
 
+  const sourceBlocks = section.message.responseBlocks.filter(
+    (block): block is typeof block & { type: 'source' } =>
+      block.type === 'source',
+  );
+
+  const sources = sourceBlocks.flatMap((block) => block.data);
+
+  const hasContent = section.parsedTextBlocks.length > 0;
+
   const { speechStatus, start, stop } = useSpeech({ text: speechMessage });
 
   const markdownOverrides: MarkdownToJSX.Options = {
@@ -72,7 +84,7 @@ const MessageBox = ({
     <div className="space-y-6">
       <div className={'w-full pt-8 break-words'}>
         <h2 className="text-black dark:text-white font-medium text-3xl lg:w-9/12">
-          {section.userMessage.content}
+          {section.message.query}
         </h2>
       </div>
 
@@ -81,21 +93,50 @@ const MessageBox = ({
           ref={dividerRef}
           className="flex flex-col space-y-6 w-full lg:w-9/12"
         >
-          {section.sourceMessage &&
-            section.sourceMessage.sources.length > 0 && (
-              <div className="flex flex-col space-y-2">
-                <div className="flex flex-row items-center space-x-2">
-                  <BookCopy className="text-black dark:text-white" size={20} />
-                  <h3 className="text-black dark:text-white font-medium text-xl">
-                    Sources
-                  </h3>
-                </div>
-                <MessageSources sources={section.sourceMessage.sources} />
+          {sources.length > 0 && (
+            <div className="flex flex-col space-y-2">
+              <div className="flex flex-row items-center space-x-2">
+                <BookCopy className="text-black dark:text-white" size={20} />
+                <h3 className="text-black dark:text-white font-medium text-xl">
+                  Sources
+                </h3>
+              </div>
+              <MessageSources sources={sources} />
+            </div>
+          )}
+
+          {section.message.responseBlocks
+            .filter(
+              (block): block is ResearchBlock =>
+                block.type === 'research' && block.data.subSteps.length > 0,
+            )
+            .map((researchBlock) => (
+              <div key={researchBlock.id} className="flex flex-col space-y-2">
+                <AssistantSteps
+                  block={researchBlock}
+                  status={section.message.status}
+                />
+              </div>
+            ))}
+
+          {section.widgets.length > 0 && <Renderer widgets={section.widgets} />}
+
+          {isLast &&
+            loading &&
+            !researchEnded &&
+            !section.message.responseBlocks.some(
+              (b) => b.type === 'research' && b.data.subSteps.length > 0,
+            ) && (
+              <div className="flex items-center gap-2 p-3 rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200">
+                <Disc3 className="w-4 h-4 text-black dark:text-white animate-spin" />
+                <span className="text-sm text-black/70 dark:text-white/70">
+                  Brainstorming...
+                </span>
               </div>
             )}
 
           <div className="flex flex-col space-y-2">
-            {section.sourceMessage && (
+            {sources.length > 0 && (
               <div className="flex flex-row items-center space-x-2">
                 <Disc3
                   className={cn(
@@ -110,7 +151,7 @@ const MessageBox = ({
               </div>
             )}
 
-            {section.assistantMessage && (
+            {hasContent && (
               <>
                 <Markdown
                   className={cn(
@@ -127,14 +168,11 @@ const MessageBox = ({
                     <div className="flex flex-row items-center -ml-2">
                       <Rewrite
                         rewrite={rewrite}
-                        messageId={section.assistantMessage.messageId}
+                        messageId={section.message.messageId}
                       />
                     </div>
                     <div className="flex flex-row items-center -mr-2">
-                      <Copy
-                        initialMessage={section.assistantMessage.content}
-                        section={section}
-                      />
+                      <Copy initialMessage={parsedMessage} section={section} />
                       <button
                         onClick={() => {
                           if (speechStatus === 'started') {
@@ -158,7 +196,7 @@ const MessageBox = ({
                 {isLast &&
                   section.suggestions &&
                   section.suggestions.length > 0 &&
-                  section.assistantMessage &&
+                  hasContent &&
                   !loading && (
                     <div className="mt-6">
                       <div className="flex flex-row items-center space-x-2 mb-4">
@@ -206,17 +244,17 @@ const MessageBox = ({
           </div>
         </div>
 
-        {section.assistantMessage && (
+        {hasContent && (
           <div className="lg:sticky lg:top-20 flex flex-col items-center space-y-3 w-full lg:w-3/12 z-30 h-full pb-4">
             <SearchImages
-              query={section.userMessage.content}
-              chatHistory={chatTurns}
-              messageId={section.assistantMessage.messageId}
+              query={section.message.query}
+              chatHistory={messages}
+              messageId={section.message.messageId}
             />
             <SearchVideos
-              chatHistory={chatTurns}
-              query={section.userMessage.content}
-              messageId={section.assistantMessage.messageId}
+              chatHistory={messages}
+              query={section.message.query}
+              messageId={section.message.messageId}
             />
           </div>
         )}

src/components/MessageInputActions/Optimization.tsx

@@ -24,7 +24,7 @@ const OptimizationModes = [
   },
   {
     key: 'quality',
-    title: 'Quality (Soon)',
+    title: 'Quality',
     description: 'Get the most thorough and accurate answer',
     icon: (
       <Star
@@ -75,13 +75,11 @@ const Optimization = () => {
                   <PopoverButton
                     onClick={() => setOptimizationMode(mode.key)}
                     key={i}
-                    disabled={mode.key === 'quality'}
                     className={cn(
                       'p-2 rounded-lg flex flex-col items-start justify-start text-start space-y-1 duration-200 cursor-pointer transition focus:outline-none',
                       optimizationMode === mode.key
                         ? 'bg-light-secondary dark:bg-dark-secondary'
                         : 'hover:bg-light-secondary dark:hover:bg-dark-secondary',
-                      mode.key === 'quality' && 'opacity-50 cursor-not-allowed',
                     )}
                   >
                     <div className="flex flex-row items-center space-x-1 text-black dark:text-white">

src/components/MessageSources.tsx

@@ -6,11 +6,11 @@ import {
   Transition,
   TransitionChild,
 } from '@headlessui/react';
-import { Document } from '@langchain/core/documents';
 import { File } from 'lucide-react';
 import { Fragment, useState } from 'react';
+import { Chunk } from '@/lib/types';
 
-const MessageSources = ({ sources }: { sources: Document[] }) => {
+const MessageSources = ({ sources }: { sources: Chunk[] }) => {
   const [isDialogOpen, setIsDialogOpen] = useState(false);
 
   const closeModal = () => {

src/components/Navbar.tsx

@@ -11,6 +11,7 @@ import {
 } from '@headlessui/react';
 import jsPDF from 'jspdf';
 import { useChat, Section } from '@/lib/hooks/useChat';
+import { SourceBlock } from '@/lib/types';
 
 const downloadFile = (filename: string, content: string, type: string) => {
   const blob = new Blob([content], { type });
@@ -28,35 +29,41 @@ const downloadFile = (filename: string, content: string, type: string) => {
 
 const exportAsMarkdown = (sections: Section[], title: string) => {
   const date = new Date(
-    sections[0]?.userMessage?.createdAt || Date.now(),
+    sections[0].message.createdAt || Date.now(),
   ).toLocaleString();
   let md = `# 💬 Chat Export: ${title}\n\n`;
   md += `*Exported on: ${date}*\n\n---\n`;
 
   sections.forEach((section, idx) => {
-    if (section.userMessage) {
-      md += `\n---\n`;
-      md += `**🧑 User**  
+    md += `\n---\n`;
+    md += `**🧑 User**  
 `;
-      md += `*${new Date(section.userMessage.createdAt).toLocaleString()}*\n\n`;
-      md += `> ${section.userMessage.content.replace(/\n/g, '\n> ')}\n`;
-    }
+    md += `*${new Date(section.message.createdAt).toLocaleString()}*\n\n`;
+    md += `> ${section.message.query.replace(/\n/g, '\n> ')}\n`;
 
-    if (section.assistantMessage) {
+    if (section.message.responseBlocks.length > 0) {
       md += `\n---\n`;
       md += `**🤖 Assistant**  
 `;
-      md += `*${new Date(section.assistantMessage.createdAt).toLocaleString()}*\n\n`;
-      md += `> ${section.assistantMessage.content.replace(/\n/g, '\n> ')}\n`;
+      md += `*${new Date(section.message.createdAt).toLocaleString()}*\n\n`;
+      md += `> ${section.message.responseBlocks
+        .filter((b) => b.type === 'text')
+        .map((block) => block.data)
+        .join('\n')
+        .replace(/\n/g, '\n> ')}\n`;
     }
 
+    const sourceResponseBlock = section.message.responseBlocks.find(
+      (block) => block.type === 'source',
+    ) as SourceBlock | undefined;
+
     if (
-      section.sourceMessage &&
-      section.sourceMessage.sources &&
-      section.sourceMessage.sources.length > 0
+      sourceResponseBlock &&
+      sourceResponseBlock.data &&
+      sourceResponseBlock.data.length > 0
     ) {
       md += `\n**Citations:**\n`;
-      section.sourceMessage.sources.forEach((src: any, i: number) => {
+      sourceResponseBlock.data.forEach((src: any, i: number) => {
         const url = src.metadata?.url || '';
         md += `- [${i + 1}] [${url}](${url})\n`;
       });
@@ -69,7 +76,7 @@ const exportAsMarkdown = (sections: Section[], title: string) => {
 const exportAsPDF = (sections: Section[], title: string) => {
   const doc = new jsPDF();
   const date = new Date(
-    sections[0]?.userMessage?.createdAt || Date.now(),
+    sections[0]?.message?.createdAt || Date.now(),
   ).toLocaleString();
   let y = 15;
   const pageHeight = doc.internal.pageSize.height;
@@ -86,44 +93,38 @@ const exportAsPDF = (sections: Section[], title: string) => {
   doc.setTextColor(30);
 
   sections.forEach((section, idx) => {
-    if (section.userMessage) {
-      if (y > pageHeight - 30) {
-        doc.addPage();
-        y = 15;
-      }
-      doc.setFont('helvetica', 'bold');
-      doc.text('User', 10, y);
-      doc.setFont('helvetica', 'normal');
-      doc.setFontSize(10);
-      doc.setTextColor(120);
-      doc.text(
-        `${new Date(section.userMessage.createdAt).toLocaleString()}`,
-        40,
-        y,
-      );
-      y += 6;
-      doc.setTextColor(30);
-      doc.setFontSize(12);
-      const userLines = doc.splitTextToSize(section.userMessage.content, 180);
-      for (let i = 0; i < userLines.length; i++) {
-        if (y > pageHeight - 20) {
-          doc.addPage();
-          y = 15;
-        }
-        doc.text(userLines[i], 12, y);
-        y += 6;
-      }
-      y += 6;
-      doc.setDrawColor(230);
-      if (y > pageHeight - 10) {
-        doc.addPage();
-        y = 15;
-      }
-      doc.line(10, y, 200, y);
-      y += 4;
+    if (y > pageHeight - 30) {
+      doc.addPage();
+      y = 15;
     }
+    doc.setFont('helvetica', 'bold');
+    doc.text('User', 10, y);
+    doc.setFont('helvetica', 'normal');
+    doc.setFontSize(10);
+    doc.setTextColor(120);
+    doc.text(`${new Date(section.message.createdAt).toLocaleString()}`, 40, y);
+    y += 6;
+    doc.setTextColor(30);
+    doc.setFontSize(12);
+    const userLines = doc.splitTextToSize(section.message.query, 180);
+    for (let i = 0; i < userLines.length; i++) {
+      if (y > pageHeight - 20) {
+        doc.addPage();
+        y = 15;
+      }
+      doc.text(userLines[i], 12, y);
+      y += 6;
+    }
+    y += 6;
+    doc.setDrawColor(230);
+    if (y > pageHeight - 10) {
+      doc.addPage();
+      y = 15;
+    }
+    doc.line(10, y, 200, y);
+    y += 4;
 
-    if (section.assistantMessage) {
+    if (section.message.responseBlocks.length > 0) {
       if (y > pageHeight - 30) {
         doc.addPage();
         y = 15;
@@ -134,7 +135,7 @@ const exportAsPDF = (sections: Section[], title: string) => {
       doc.setFontSize(10);
       doc.setTextColor(120);
       doc.text(
-        `${new Date(section.assistantMessage.createdAt).toLocaleString()}`,
+        `${new Date(section.message.createdAt).toLocaleString()}`,
         40,
         y,
       );
@@ -142,7 +143,7 @@ const exportAsPDF = (sections: Section[], title: string) => {
       doc.setTextColor(30);
       doc.setFontSize(12);
       const assistantLines = doc.splitTextToSize(
-        section.assistantMessage.content,
+        section.parsedTextBlocks.join('\n'),
         180,
       );
       for (let i = 0; i < assistantLines.length; i++) {
@@ -154,10 +155,14 @@ const exportAsPDF = (sections: Section[], title: string) => {
         y += 6;
       }
 
+      const sourceResponseBlock = section.message.responseBlocks.find(
+        (block) => block.type === 'source',
+      ) as SourceBlock | undefined;
+
       if (
-        section.sourceMessage &&
-        section.sourceMessage.sources &&
-        section.sourceMessage.sources.length > 0
+        sourceResponseBlock &&
+        sourceResponseBlock.data &&
+        sourceResponseBlock.data.length > 0
       ) {
         doc.setFontSize(11);
         doc.setTextColor(80);
@@ -167,7 +172,7 @@ const exportAsPDF = (sections: Section[], title: string) => {
         }
         doc.text('Citations:', 12, y);
         y += 5;
-        section.sourceMessage.sources.forEach((src: any, i: number) => {
+        sourceResponseBlock.data.forEach((src: any, i: number) => {
           const url = src.metadata?.url || '';
           if (y > pageHeight - 15) {
             doc.addPage();
@@ -198,15 +203,15 @@ const Navbar = () => {
   const { sections, chatId } = useChat();
 
   useEffect(() => {
-    if (sections.length > 0 && sections[0].userMessage) {
+    if (sections.length > 0 && sections[0].message) {
       const newTitle =
-        sections[0].userMessage.content.length > 20
-          ? `${sections[0].userMessage.content.substring(0, 20).trim()}...`
-          : sections[0].userMessage.content;
+        sections[0].message.query.substring(0, 30) + '...' ||
+        'New Conversation';
+
       setTitle(newTitle);
       const newTimeAgo = formatTimeDifference(
         new Date(),
-        sections[0].userMessage.createdAt,
+        sections[0].message.createdAt,
       );
       setTimeAgo(newTimeAgo);
     }
@@ -214,10 +219,10 @@ const Navbar = () => {
 
   useEffect(() => {
     const intervalId = setInterval(() => {
-      if (sections.length > 0 && sections[0].userMessage) {
+      if (sections.length > 0 && sections[0].message) {
         const newTimeAgo = formatTimeDifference(
           new Date(),
-          sections[0].userMessage.createdAt,
+          sections[0].message.createdAt,
         );
         setTimeAgo(newTimeAgo);
       }

src/components/WeatherWidget.tsx

@@ -91,7 +91,7 @@ const WeatherWidget = () => {
       setData({
         temperature: data.temperature,
         condition: data.condition,
-        location: location.city,
+        location: 'Mars',
         humidity: data.humidity,
         windSpeed: data.windSpeed,
         icon: data.icon,

src/components/Widgets/Calculation.tsx

@@ -0,0 +1,54 @@
+'use client';
+
+import { Calculator, Equal } from 'lucide-react';
+
+type CalculationWidgetProps = {
+  expression: string;
+  result: number;
+};
+
+const Calculation = ({ expression, result }: CalculationWidgetProps) => {
+  return (
+    <div className="rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 overflow-hidden shadow-sm">
+      <div className="flex items-center gap-2 p-3 bg-light-100/50 dark:bg-dark-100/50 border-b border-light-200 dark:border-dark-200">
+        <div className="rounded-full p-1.5 bg-light-100 dark:bg-dark-100">
+          <Calculator className="w-4 h-4 text-black/70 dark:text-white/70" />
+        </div>
+        <span className="text-sm font-medium text-black dark:text-white">
+          Calculation
+        </span>
+      </div>
+
+      <div className="p-4 space-y-3">
+        <div>
+          <div className="flex items-center gap-1.5 mb-1.5">
+            <span className="text-xs text-black/50 dark:text-white/50 font-medium">
+              Expression
+            </span>
+          </div>
+          <div className="bg-light-100 dark:bg-dark-100 rounded-md p-2.5 border border-light-200 dark:border-dark-200">
+            <code className="text-sm text-black dark:text-white font-mono break-all">
+              {expression}
+            </code>
+          </div>
+        </div>
+
+        <div>
+          <div className="flex items-center gap-1.5 mb-1.5">
+            <Equal className="w-3.5 h-3.5 text-black/50 dark:text-white/50" />
+            <span className="text-xs text-black/50 dark:text-white/50 font-medium">
+              Result
+            </span>
+          </div>
+          <div className="bg-gradient-to-br from-light-100 to-light-secondary dark:from-dark-100 dark:to-dark-secondary rounded-md p-4 border-2 border-light-200 dark:border-dark-200">
+            <div className="text-4xl font-bold text-black dark:text-white font-mono tabular-nums">
+              {result.toLocaleString()}
+            </div>
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+};
+
+export default Calculation;

src/components/Widgets/Renderer.tsx

@@ -0,0 +1,76 @@
+import React from 'react';
+import { Widget } from '../ChatWindow';
+import Weather from './Weather';
+import Calculation from './Calculation';
+import Stock from './Stock';
+
+const Renderer = ({ widgets }: { widgets: Widget[] }) => {
+  return widgets.map((widget, index) => {
+    switch (widget.widgetType) {
+      case 'weather':
+        return (
+          <Weather
+            key={index}
+            location={widget.params.location}
+            current={widget.params.current}
+            daily={widget.params.daily}
+            timezone={widget.params.timezone}
+          />
+        );
+      case 'calculation_result':
+        return (
+          <Calculation
+            expression={widget.params.expression}
+            result={widget.params.result}
+            key={index}
+          />
+        );
+      case 'stock':
+        return (
+          <Stock
+            key={index}
+            symbol={widget.params.symbol}
+            shortName={widget.params.shortName}
+            longName={widget.params.longName}
+            exchange={widget.params.exchange}
+            currency={widget.params.currency}
+            marketState={widget.params.marketState}
+            regularMarketPrice={widget.params.regularMarketPrice}
+            regularMarketChange={widget.params.regularMarketChange}
+            regularMarketChangePercent={
+              widget.params.regularMarketChangePercent
+            }
+            regularMarketPreviousClose={
+              widget.params.regularMarketPreviousClose
+            }
+            regularMarketOpen={widget.params.regularMarketOpen}
+            regularMarketDayHigh={widget.params.regularMarketDayHigh}
+            regularMarketDayLow={widget.params.regularMarketDayLow}
+            regularMarketVolume={widget.params.regularMarketVolume}
+            averageDailyVolume3Month={widget.params.averageDailyVolume3Month}
+            marketCap={widget.params.marketCap}
+            fiftyTwoWeekLow={widget.params.fiftyTwoWeekLow}
+            fiftyTwoWeekHigh={widget.params.fiftyTwoWeekHigh}
+            trailingPE={widget.params.trailingPE}
+            forwardPE={widget.params.forwardPE}
+            dividendYield={widget.params.dividendYield}
+            earningsPerShare={widget.params.earningsPerShare}
+            website={widget.params.website}
+            postMarketPrice={widget.params.postMarketPrice}
+            postMarketChange={widget.params.postMarketChange}
+            postMarketChangePercent={widget.params.postMarketChangePercent}
+            preMarketPrice={widget.params.preMarketPrice}
+            preMarketChange={widget.params.preMarketChange}
+            preMarketChangePercent={widget.params.preMarketChangePercent}
+            chartData={widget.params.chartData}
+            comparisonData={widget.params.comparisonData}
+            error={widget.params.error}
+          />
+        );
+      default:
+        return <div key={index}>Unknown widget type: {widget.widgetType}</div>;
+    }
+  });
+};
+
+export default Renderer;

src/components/Widgets/Stock.tsx

@@ -0,0 +1,517 @@
+'use client';
+
+import { Clock, ArrowUpRight, ArrowDownRight, Minus } from 'lucide-react';
+import { useEffect, useRef, useState } from 'react';
+import {
+  createChart,
+  ColorType,
+  LineStyle,
+  BaselineSeries,
+  LineSeries,
+} from 'lightweight-charts';
+
+type StockWidgetProps = {
+  symbol: string;
+  shortName: string;
+  longName?: string;
+  exchange?: string;
+  currency?: string;
+  marketState?: string;
+  regularMarketPrice?: number;
+  regularMarketChange?: number;
+  regularMarketChangePercent?: number;
+  regularMarketPreviousClose?: number;
+  regularMarketOpen?: number;
+  regularMarketDayHigh?: number;
+  regularMarketDayLow?: number;
+  regularMarketVolume?: number;
+  averageDailyVolume3Month?: number;
+  marketCap?: number;
+  fiftyTwoWeekLow?: number;
+  fiftyTwoWeekHigh?: number;
+  trailingPE?: number;
+  forwardPE?: number;
+  dividendYield?: number;
+  earningsPerShare?: number;
+  website?: string;
+  postMarketPrice?: number;
+  postMarketChange?: number;
+  postMarketChangePercent?: number;
+  preMarketPrice?: number;
+  preMarketChange?: number;
+  preMarketChangePercent?: number;
+  chartData?: {
+    '1D'?: { timestamps: number[]; prices: number[] } | null;
+    '5D'?: { timestamps: number[]; prices: number[] } | null;
+    '1M'?: { timestamps: number[]; prices: number[] } | null;
+    '3M'?: { timestamps: number[]; prices: number[] } | null;
+    '6M'?: { timestamps: number[]; prices: number[] } | null;
+    '1Y'?: { timestamps: number[]; prices: number[] } | null;
+    MAX?: { timestamps: number[]; prices: number[] } | null;
+  } | null;
+  comparisonData?: Array<{
+    ticker: string;
+    name: string;
+    chartData: {
+      '1D'?: { timestamps: number[]; prices: number[] } | null;
+      '5D'?: { timestamps: number[]; prices: number[] } | null;
+      '1M'?: { timestamps: number[]; prices: number[] } | null;
+      '3M'?: { timestamps: number[]; prices: number[] } | null;
+      '6M'?: { timestamps: number[]; prices: number[] } | null;
+      '1Y'?: { timestamps: number[]; prices: number[] } | null;
+      MAX?: { timestamps: number[]; prices: number[] } | null;
+    };
+  }> | null;
+  error?: string;
+};
+
+const formatNumber = (num: number | undefined, decimals = 2): string => {
+  if (num === undefined || num === null) return 'N/A';
+  return num.toLocaleString(undefined, {
+    minimumFractionDigits: decimals,
+    maximumFractionDigits: decimals,
+  });
+};
+
+const formatLargeNumber = (num: number | undefined): string => {
+  if (num === undefined || num === null) return 'N/A';
+  if (num >= 1e12) return `$${(num / 1e12).toFixed(2)}T`;
+  if (num >= 1e9) return `$${(num / 1e9).toFixed(2)}B`;
+  if (num >= 1e6) return `$${(num / 1e6).toFixed(2)}M`;
+  if (num >= 1e3) return `$${(num / 1e3).toFixed(2)}K`;
+  return `$${num.toFixed(2)}`;
+};
+
+const Stock = (props: StockWidgetProps) => {
+  const [isDarkMode, setIsDarkMode] = useState(false);
+  const [selectedTimeframe, setSelectedTimeframe] = useState<
+    '1D' | '5D' | '1M' | '3M' | '6M' | '1Y' | 'MAX'
+  >('1M');
+  const chartContainerRef = useRef<HTMLDivElement>(null);
+
+  useEffect(() => {
+    const checkDarkMode = () => {
+      setIsDarkMode(document.documentElement.classList.contains('dark'));
+    };
+
+    checkDarkMode();
+
+    const observer = new MutationObserver(checkDarkMode);
+    observer.observe(document.documentElement, {
+      attributes: true,
+      attributeFilter: ['class'],
+    });
+
+    return () => observer.disconnect();
+  }, []);
+
+  useEffect(() => {
+    const currentChartData = props.chartData?.[selectedTimeframe];
+    if (
+      !chartContainerRef.current ||
+      !currentChartData ||
+      currentChartData.timestamps.length === 0
+    ) {
+      return;
+    }
+
+    const chart = createChart(chartContainerRef.current, {
+      width: chartContainerRef.current.clientWidth,
+      height: 280,
+      layout: {
+        background: { type: ColorType.Solid, color: 'transparent' },
+        textColor: isDarkMode ? '#6b7280' : '#9ca3af',
+        fontSize: 11,
+        attributionLogo: false,
+      },
+      grid: {
+        vertLines: {
+          color: isDarkMode ? '#21262d' : '#e8edf1',
+          style: LineStyle.Solid,
+        },
+        horzLines: {
+          color: isDarkMode ? '#21262d' : '#e8edf1',
+          style: LineStyle.Solid,
+        },
+      },
+      crosshair: {
+        vertLine: {
+          color: isDarkMode ? '#30363d' : '#d0d7de',
+          labelVisible: false,
+        },
+        horzLine: {
+          color: isDarkMode ? '#30363d' : '#d0d7de',
+          labelVisible: true,
+        },
+      },
+      rightPriceScale: {
+        borderVisible: false,
+        visible: false,
+      },
+      leftPriceScale: {
+        borderVisible: false,
+        visible: true,
+      },
+      timeScale: {
+        borderVisible: false,
+        timeVisible: false,
+      },
+      handleScroll: false,
+      handleScale: false,
+    });
+
+    const prices = currentChartData.prices;
+    let baselinePrice: number;
+
+    if (selectedTimeframe === '1D') {
+      baselinePrice = props.regularMarketPreviousClose ?? prices[0];
+    } else {
+      baselinePrice = prices[0];
+    }
+
+    const baselineSeries = chart.addSeries(BaselineSeries);
+
+    baselineSeries.applyOptions({
+      baseValue: { type: 'price', price: baselinePrice },
+      topLineColor: isDarkMode ? '#14b8a6' : '#0d9488',
+      topFillColor1: isDarkMode
+        ? 'rgba(20, 184, 166, 0.28)'
+        : 'rgba(13, 148, 136, 0.24)',
+      topFillColor2: isDarkMode
+        ? 'rgba(20, 184, 166, 0.05)'
+        : 'rgba(13, 148, 136, 0.05)',
+      bottomLineColor: isDarkMode ? '#f87171' : '#dc2626',
+      bottomFillColor1: isDarkMode
+        ? 'rgba(248, 113, 113, 0.05)'
+        : 'rgba(220, 38, 38, 0.05)',
+      bottomFillColor2: isDarkMode
+        ? 'rgba(248, 113, 113, 0.28)'
+        : 'rgba(220, 38, 38, 0.24)',
+      lineWidth: 2,
+      crosshairMarkerVisible: true,
+      crosshairMarkerRadius: 4,
+      crosshairMarkerBorderColor: '',
+      crosshairMarkerBackgroundColor: '',
+    });
+
+    const data = currentChartData.timestamps.map((timestamp, index) => {
+      const price = currentChartData.prices[index];
+      return {
+        time: (timestamp / 1000) as any,
+        value: price,
+      };
+    });
+
+    baselineSeries.setData(data);
+
+    const comparisonColors = ['#8b5cf6', '#f59e0b', '#ec4899'];
+    if (props.comparisonData && props.comparisonData.length > 0) {
+      props.comparisonData.forEach((comp, index) => {
+        const compChartData = comp.chartData[selectedTimeframe];
+        if (compChartData && compChartData.prices.length > 0) {
+          const compData = compChartData.timestamps.map((timestamp, i) => ({
+            time: (timestamp / 1000) as any,
+            value: compChartData.prices[i],
+          }));
+
+          const compSeries = chart.addSeries(LineSeries);
+          compSeries.applyOptions({
+            color: comparisonColors[index] || '#6b7280',
+            lineWidth: 2,
+            crosshairMarkerVisible: true,
+            crosshairMarkerRadius: 4,
+            priceScaleId: 'left',
+          });
+          compSeries.setData(compData);
+        }
+      });
+    }
+
+    chart.timeScale().fitContent();
+
+    const handleResize = () => {
+      if (chartContainerRef.current) {
+        chart.applyOptions({
+          width: chartContainerRef.current.clientWidth,
+        });
+      }
+    };
+
+    window.addEventListener('resize', handleResize);
+
+    return () => {
+      window.removeEventListener('resize', handleResize);
+      chart.remove();
+    };
+  }, [
+    props.chartData,
+    props.comparisonData,
+    selectedTimeframe,
+    isDarkMode,
+    props.regularMarketPreviousClose,
+  ]);
+
+  const isPositive = (props.regularMarketChange ?? 0) >= 0;
+  const isMarketOpen = props.marketState === 'REGULAR';
+  const isPreMarket = props.marketState === 'PRE';
+  const isPostMarket = props.marketState === 'POST';
+
+  const displayPrice = isPostMarket
+    ? props.postMarketPrice ?? props.regularMarketPrice
+    : isPreMarket
+      ? props.preMarketPrice ?? props.regularMarketPrice
+      : props.regularMarketPrice;
+
+  const displayChange = isPostMarket
+    ? props.postMarketChange ?? props.regularMarketChange
+    : isPreMarket
+      ? props.preMarketChange ?? props.regularMarketChange
+      : props.regularMarketChange;
+
+  const displayChangePercent = isPostMarket
+    ? props.postMarketChangePercent ?? props.regularMarketChangePercent
+    : isPreMarket
+      ? props.preMarketChangePercent ?? props.regularMarketChangePercent
+      : props.regularMarketChangePercent;
+
+  const changeColor = isPositive
+    ? 'text-green-600 dark:text-green-400'
+    : 'text-red-600 dark:text-red-400';
+
+  if (props.error) {
+    return (
+      <div className="rounded-lg bg-light-secondary dark:bg-dark-secondary border border-light-200 dark:border-dark-200 p-4">
+        <p className="text-sm text-black dark:text-white">
+          Error: {props.error}
+        </p>
+      </div>
+    );
+  }
+
+  return (
+    <div className="rounded-lg border border-light-200 dark:border-dark-200 overflow-hidden">
+      <div className="p-4 space-y-4">
+        <div className="flex items-start justify-between gap-4 pb-4 border-b border-light-200 dark:border-dark-200">
+          <div className="flex-1">
+            <div className="flex items-center gap-2 mb-1">
+              {props.website && (
+                <img
+                  src={`https://logo.clearbit.com/${new URL(props.website).hostname}`}
+                  alt={`${props.symbol} logo`}
+                  className="w-8 h-8 rounded-lg"
+                  onError={(e) => {
+                    (e.target as HTMLImageElement).style.display = 'none';
+                  }}
+                />
+              )}
+              <h3 className="text-2xl font-bold text-black dark:text-white">
+                {props.symbol}
+              </h3>
+              {props.exchange && (
+                <span className="px-2 py-0.5 text-xs font-medium rounded bg-light-100 dark:bg-dark-100 text-black/60 dark:text-white/60">
+                  {props.exchange}
+                </span>
+              )}
+              {isMarketOpen && (
+                <div className="flex items-center gap-1.5 px-2 py-0.5 rounded-full bg-green-100 dark:bg-green-950/40 border border-green-300 dark:border-green-800">
+                  <div className="w-1.5 h-1.5 rounded-full bg-green-500 animate-pulse" />
+                  <span className="text-xs font-medium text-green-700 dark:text-green-400">
+                    Live
+                  </span>
+                </div>
+              )}
+              {isPreMarket && (
+                <div className="flex items-center gap-1.5 px-2 py-0.5 rounded-full bg-blue-100 dark:bg-blue-950/40 border border-blue-300 dark:border-blue-800">
+                  <Clock className="w-3 h-3 text-blue-600 dark:text-blue-400" />
+                  <span className="text-xs font-medium text-blue-700 dark:text-blue-400">
+                    Pre-Market
+                  </span>
+                </div>
+              )}
+              {isPostMarket && (
+                <div className="flex items-center gap-1.5 px-2 py-0.5 rounded-full bg-orange-100 dark:bg-orange-950/40 border border-orange-300 dark:border-orange-800">
+                  <Clock className="w-3 h-3 text-orange-600 dark:text-orange-400" />
+                  <span className="text-xs font-medium text-orange-700 dark:text-orange-400">
+                    After Hours
+                  </span>
+                </div>
+              )}
+            </div>
+            <p className="text-sm text-black/60 dark:text-white/60">
+              {props.longName || props.shortName}
+            </p>
+          </div>
+
+          <div className="text-right">
+            <div className="flex items-baseline gap-2 mb-1">
+              <span className="text-3xl font-medium text-black dark:text-white">
+                {props.currency === 'USD' ? '$' : ''}
+                {formatNumber(displayPrice)}
+              </span>
+            </div>
+            <div
+              className={`flex items-center justify-end gap-1 ${changeColor}`}
+            >
+              {isPositive ? (
+                <ArrowUpRight className="w-4 h-4" />
+              ) : displayChange === 0 ? (
+                <Minus className="w-4 h-4" />
+              ) : (
+                <ArrowDownRight className="w-4 h-4" />
+              )}
+              <span className="text-lg font-normal">
+                {displayChange !== undefined && displayChange >= 0 ? '+' : ''}
+                {formatNumber(displayChange)}
+              </span>
+              <span className="text-sm font-normal">
+                (
+                {displayChangePercent !== undefined && displayChangePercent >= 0
+                  ? '+'
+                  : ''}
+                {formatNumber(displayChangePercent)}%)
+              </span>
+            </div>
+          </div>
+        </div>
+
+        {props.chartData && (
+          <div className="bg-light-secondary dark:bg-dark-secondary rounded-lg overflow-hidden">
+            <div className="flex items-center justify-between p-3 border-b border-light-200 dark:border-dark-200">
+              <div className="flex items-center gap-1">
+                {(['1D', '5D', '1M', '3M', '6M', '1Y', 'MAX'] as const).map(
+                  (timeframe) => (
+                    <button
+                      key={timeframe}
+                      onClick={() => setSelectedTimeframe(timeframe)}
+                      disabled={!props.chartData?.[timeframe]}
+                      className={`px-3 py-1.5 text-xs font-medium rounded transition-colors ${
+                        selectedTimeframe === timeframe
+                          ? 'bg-black/10 dark:bg-white/10 text-black dark:text-white'
+                          : 'text-black/50 dark:text-white/50 hover:text-black/80 dark:hover:text-white/80'
+                      } disabled:opacity-30 disabled:cursor-not-allowed`}
+                    >
+                      {timeframe}
+                    </button>
+                  ),
+                )}
+              </div>
+
+              {props.comparisonData && props.comparisonData.length > 0 && (
+                <div className="flex items-center gap-3 ml-auto">
+                  <span className="text-xs text-black/50 dark:text-white/50">
+                    {props.symbol}
+                  </span>
+                  {props.comparisonData.map((comp, index) => {
+                    const colors = ['#8b5cf6', '#f59e0b', '#ec4899'];
+                    return (
+                      <div
+                        key={comp.ticker}
+                        className="flex items-center gap-1.5"
+                      >
+                        <div
+                          className="w-2 h-2 rounded-full"
+                          style={{ backgroundColor: colors[index] }}
+                        />
+                        <span className="text-xs text-black/70 dark:text-white/70">
+                          {comp.ticker}
+                        </span>
+                      </div>
+                    );
+                  })}
+                </div>
+              )}
+            </div>
+
+            <div className="p-4">
+              <div ref={chartContainerRef} />
+            </div>
+
+            <div className="grid grid-cols-3 border-t border-light-200 dark:border-dark-200">
+              <div className="flex justify-between p-3 border-r border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  Prev Close
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  ${formatNumber(props.regularMarketPreviousClose)}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-r border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  52W Range
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  ${formatNumber(props.fiftyTwoWeekLow, 2)}-$
+                  {formatNumber(props.fiftyTwoWeekHigh, 2)}
+                </span>
+              </div>
+              <div className="flex justify-between p-3">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  Market Cap
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  {formatLargeNumber(props.marketCap)}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  Open
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  ${formatNumber(props.regularMarketOpen)}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  P/E Ratio
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  {props.trailingPE ? formatNumber(props.trailingPE, 2) : 'N/A'}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-t border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  Dividend Yield
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  {props.dividendYield
+                    ? `${formatNumber(props.dividendYield * 100, 2)}%`
+                    : 'N/A'}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  Day Range
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  ${formatNumber(props.regularMarketDayLow, 2)}-$
+                  {formatNumber(props.regularMarketDayHigh, 2)}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-t border-r border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  Volume
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  {formatLargeNumber(props.regularMarketVolume)}
+                </span>
+              </div>
+              <div className="flex justify-between p-3 border-t border-light-200 dark:border-dark-200">
+                <span className="text-xs text-black/50 dark:text-white/50">
+                  EPS
+                </span>
+                <span className="text-xs text-black dark:text-white font-medium">
+                  $
+                  {props.earningsPerShare
+                    ? formatNumber(props.earningsPerShare, 2)
+                    : 'N/A'}
+                </span>
+              </div>
+            </div>
+          </div>
+        )}
+      </div>
+    </div>
+  );
+};
+
+export default Stock;

src/components/Widgets/Weather.tsx

@@ -0,0 +1,408 @@
+'use client';
+
+import { Wind, Droplets, Gauge } from 'lucide-react';
+import { useMemo, useEffect, useState } from 'react';
+
+type WeatherWidgetProps = {
+  location: string;
+  current: {
+    time: string;
+    temperature_2m: number;
+    relative_humidity_2m: number;
+    apparent_temperature: number;
+    is_day: number;
+    precipitation: number;
+    weather_code: number;
+    wind_speed_10m: number;
+    wind_direction_10m: number;
+    wind_gusts_10m?: number;
+  };
+  daily: {
+    time: string[];
+    weather_code: number[];
+    temperature_2m_max: number[];
+    temperature_2m_min: number[];
+    precipitation_probability_max: number[];
+  };
+  timezone: string;
+};
+
+const getWeatherInfo = (code: number, isDay: boolean, isDarkMode: boolean) => {
+  const dayNight = isDay ? 'day' : 'night';
+
+  const weatherMap: Record<
+    number,
+    { icon: string; description: string; gradient: string }
+  > = {
+    0: {
+      icon: `clear-${dayNight}.svg`,
+      description: 'Clear',
+      gradient: isDarkMode
+        ? isDay
+          ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E8F1FA, #7A9DBF 35%, #4A7BA8 60%, #2F5A88)'
+          : 'radial-gradient(ellipse 150% 100% at 50% 100%, #5A6A7E, #3E4E63 40%, #2A3544 65%, #1A2230)'
+        : isDay
+          ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #DBEAFE 30%, #93C5FD 60%, #60A5FA)'
+          : 'radial-gradient(ellipse 150% 100% at 50% 100%, #7B8694, #475569 45%, #334155 70%, #1E293B)',
+    },
+    1: {
+      icon: `clear-${dayNight}.svg`,
+      description: 'Mostly Clear',
+      gradient: isDarkMode
+        ? isDay
+          ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E8F1FA, #7A9DBF 35%, #4A7BA8 60%, #2F5A88)'
+          : 'radial-gradient(ellipse 150% 100% at 50% 100%, #5A6A7E, #3E4E63 40%, #2A3544 65%, #1A2230)'
+        : isDay
+          ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #DBEAFE 30%, #93C5FD 60%, #60A5FA)'
+          : 'radial-gradient(ellipse 150% 100% at 50% 100%, #7B8694, #475569 45%, #334155 70%, #1E293B)',
+    },
+    2: {
+      icon: `cloudy-1-${dayNight}.svg`,
+      description: 'Partly Cloudy',
+      gradient: isDarkMode
+        ? isDay
+          ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4E1ED, #8BA3B8 35%, #617A93 60%, #426070)'
+          : 'radial-gradient(ellipse 150% 100% at 50% 100%, #6B7583, #4A5563 40%, #3A4450 65%, #2A3340)'
+        : isDay
+          ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #E0F2FE 28%, #BFDBFE 58%, #93C5FD)'
+          : 'radial-gradient(ellipse 150% 100% at 50% 100%, #8B99AB, #64748B 45%, #475569 70%, #334155)',
+    },
+    3: {
+      icon: `cloudy-1-${dayNight}.svg`,
+      description: 'Cloudy',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8C3CF, #758190 38%, #546270 65%, #3D4A58)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #F5F8FA, #CBD5E1 32%, #94A3B8 65%, #64748B)',
+    },
+    45: {
+      icon: `fog-${dayNight}.svg`,
+      description: 'Foggy',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #C5CDD8, #8892A0 38%, #697380 65%, #4F5A68)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #E2E8F0 30%, #CBD5E1 62%, #94A3B8)',
+    },
+    48: {
+      icon: `fog-${dayNight}.svg`,
+      description: 'Rime Fog',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #C5CDD8, #8892A0 38%, #697380 65%, #4F5A68)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #E2E8F0 30%, #CBD5E1 62%, #94A3B8)',
+    },
+    51: {
+      icon: `rainy-1-${dayNight}.svg`,
+      description: 'Light Drizzle',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8D4E5, #6FA4C5 35%, #4A85AC 60%, #356A8E)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5FBFF, #A5F3FC 28%, #67E8F9 60%, #22D3EE)',
+    },
+    53: {
+      icon: `rainy-1-${dayNight}.svg`,
+      description: 'Drizzle',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8D4E5, #6FA4C5 35%, #4A85AC 60%, #356A8E)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5FBFF, #A5F3FC 28%, #67E8F9 60%, #22D3EE)',
+    },
+    55: {
+      icon: `rainy-2-${dayNight}.svg`,
+      description: 'Heavy Drizzle',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #A5C5D8, #5E92B0 35%, #3F789D 60%, #2A5F82)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4F3FF, #7DD3FC 30%, #38BDF8 62%, #0EA5E9)',
+    },
+    61: {
+      icon: `rainy-2-${dayNight}.svg`,
+      description: 'Light Rain',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #A5C5D8, #5E92B0 35%, #3F789D 60%, #2A5F82)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4F3FF, #7DD3FC 30%, #38BDF8 62%, #0EA5E9)',
+    },
+    63: {
+      icon: `rainy-2-${dayNight}.svg`,
+      description: 'Rain',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #8DB3C8, #4D819F 38%, #326A87 65%, #215570)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8E8FF, #38BDF8 32%, #0EA5E9 65%, #0284C7)',
+    },
+    65: {
+      icon: `rainy-3-${dayNight}.svg`,
+      description: 'Heavy Rain',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #7BA3B8, #3D6F8A 38%, #295973 65%, #1A455D)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #9CD9F5, #0EA5E9 32%, #0284C7 65%, #0369A1)',
+    },
+    71: {
+      icon: `snowy-1-${dayNight}.svg`,
+      description: 'Light Snow',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5F0FA, #9BB5CE 32%, #7496B8 58%, #527A9E)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #F0F9FF 25%, #E0F2FE 55%, #BAE6FD)',
+    },
+    73: {
+      icon: `snowy-2-${dayNight}.svg`,
+      description: 'Snow',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4E5F3, #85A1BD 35%, #6584A8 60%, #496A8E)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #FAFEFF, #E0F2FE 28%, #BAE6FD 60%, #7DD3FC)',
+    },
+    75: {
+      icon: `snowy-3-${dayNight}.svg`,
+      description: 'Heavy Snow',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #BDD8EB, #6F92AE 35%, #4F7593 60%, #365A78)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #F0FAFF, #BAE6FD 30%, #7DD3FC 62%, #38BDF8)',
+    },
+    77: {
+      icon: `snowy-1-${dayNight}.svg`,
+      description: 'Snow Grains',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #E5F0FA, #9BB5CE 32%, #7496B8 58%, #527A9E)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #FFFFFF, #F0F9FF 25%, #E0F2FE 55%, #BAE6FD)',
+    },
+    80: {
+      icon: `rainy-2-${dayNight}.svg`,
+      description: 'Light Showers',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #A5C5D8, #5E92B0 35%, #3F789D 60%, #2A5F82)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4F3FF, #7DD3FC 30%, #38BDF8 62%, #0EA5E9)',
+    },
+    81: {
+      icon: `rainy-2-${dayNight}.svg`,
+      description: 'Showers',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #8DB3C8, #4D819F 38%, #326A87 65%, #215570)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #B8E8FF, #38BDF8 32%, #0EA5E9 65%, #0284C7)',
+    },
+    82: {
+      icon: `rainy-3-${dayNight}.svg`,
+      description: 'Heavy Showers',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #7BA3B8, #3D6F8A 38%, #295973 65%, #1A455D)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #9CD9F5, #0EA5E9 32%, #0284C7 65%, #0369A1)',
+    },
+    85: {
+      icon: `snowy-2-${dayNight}.svg`,
+      description: 'Light Snow Showers',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #D4E5F3, #85A1BD 35%, #6584A8 60%, #496A8E)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #FAFEFF, #E0F2FE 28%, #BAE6FD 60%, #7DD3FC)',
+    },
+    86: {
+      icon: `snowy-3-${dayNight}.svg`,
+      description: 'Snow Showers',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #BDD8EB, #6F92AE 35%, #4F7593 60%, #365A78)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #F0FAFF, #BAE6FD 30%, #7DD3FC 62%, #38BDF8)',
+    },
+    95: {
+      icon: `scattered-thunderstorms-${dayNight}.svg`,
+      description: 'Thunderstorm',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #8A95A3, #5F6A7A 38%, #475260 65%, #2F3A48)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #C8D1DD, #94A3B8 32%, #64748B 65%, #475569)',
+    },
+    96: {
+      icon: 'severe-thunderstorm.svg',
+      description: 'Thunderstorm + Hail',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #7A8593, #515C6D 38%, #3A4552 65%, #242D3A)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #B0BBC8, #64748B 32%, #475569 65%, #334155)',
+    },
+    99: {
+      icon: 'severe-thunderstorm.svg',
+      description: 'Severe Thunderstorm',
+      gradient: isDarkMode
+        ? 'radial-gradient(ellipse 150% 100% at 50% 100%, #6A7583, #434E5D 40%, #2F3A47 68%, #1C2530)'
+        : 'radial-gradient(ellipse 150% 100% at 50% 100%, #9BA8B8, #475569 35%, #334155 68%, #1E293B)',
+    },
+  };
+
+  return weatherMap[code] || weatherMap[0];
+};
+
+const Weather = ({
+  location,
+  current,
+  daily,
+  timezone,
+}: WeatherWidgetProps) => {
+  const [isDarkMode, setIsDarkMode] = useState(false);
+
+  useEffect(() => {
+    const checkDarkMode = () => {
+      setIsDarkMode(document.documentElement.classList.contains('dark'));
+    };
+
+    checkDarkMode();
+
+    const observer = new MutationObserver(checkDarkMode);
+    observer.observe(document.documentElement, {
+      attributes: true,
+      attributeFilter: ['class'],
+    });
+
+    return () => observer.disconnect();
+  }, []);
+
+  const weatherInfo = useMemo(
+    () =>
+      getWeatherInfo(
+        current?.weather_code || 0,
+        current?.is_day === 1,
+        isDarkMode,
+      ),
+    [current?.weather_code, current?.is_day, isDarkMode],
+  );
+
+  const forecast = useMemo(() => {
+    if (!daily?.time || daily.time.length === 0) return [];
+
+    return daily.time.slice(1, 7).map((time, idx) => {
+      const date = new Date(time);
+      const dayName = date.toLocaleDateString('en-US', { weekday: 'short' });
+      const isDay = true;
+      const weatherCode = daily.weather_code[idx + 1];
+      const info = getWeatherInfo(weatherCode, isDay, isDarkMode);
+
+      return {
+        day: dayName,
+        icon: info.icon,
+        high: Math.round(daily.temperature_2m_max[idx + 1]),
+        low: Math.round(daily.temperature_2m_min[idx + 1]),
+        highF: Math.round((daily.temperature_2m_max[idx + 1] * 9) / 5 + 32),
+        lowF: Math.round((daily.temperature_2m_min[idx + 1] * 9) / 5 + 32),
+        precipitation: daily.precipitation_probability_max[idx + 1] || 0,
+      };
+    });
+  }, [daily, isDarkMode]);
+
+  if (!current || !daily || !daily.time || daily.time.length === 0) {
+    return (
+      <div className="relative overflow-hidden rounded-lg shadow-md bg-gray-200 dark:bg-gray-800">
+        <div className="p-4 text-black dark:text-white">
+          <p className="text-sm">Weather data unavailable for {location}</p>
+        </div>
+      </div>
+    );
+  }
+
+  return (
+    <div className="relative overflow-hidden rounded-lg shadow-md">
+      <div
+        className="absolute inset-0"
+        style={{
+          background: weatherInfo.gradient,
+        }}
+      />
+
+      <div className="relative p-4 text-gray-800 dark:text-white">
+        <div className="flex items-start justify-between mb-3">
+          <div className="flex items-center gap-3">
+            <img
+              src={`/weather-ico/${weatherInfo.icon}`}
+              alt={weatherInfo.description}
+              className="w-16 h-16 drop-shadow-lg"
+            />
+            <div>
+              <div className="flex items-baseline gap-1">
+                <span className="text-4xl font-bold drop-shadow-md">
+                  {Math.round(current.temperature_2m)}°
+                </span>
+                <span className="text-lg">F C</span>
+              </div>
+              <p className="text-sm font-medium drop-shadow mt-0.5">
+                {weatherInfo.description}
+              </p>
+            </div>
+          </div>
+          <div className="text-right">
+            <p className="text-xs font-medium opacity-90">
+              {Math.round(daily.temperature_2m_max[0])}°{' '}
+              {Math.round(daily.temperature_2m_min[0])}°
+            </p>
+          </div>
+        </div>
+
+        <div className="mb-3 pb-3 border-b border-gray-800/20 dark:border-white/20">
+          <h3 className="text-base font-semibold drop-shadow-md">{location}</h3>
+          <p className="text-xs text-gray-700 dark:text-white/80 drop-shadow mt-0.5">
+            {new Date(current.time).toLocaleString('en-US', {
+              weekday: 'short',
+              hour: 'numeric',
+              minute: '2-digit',
+            })}
+          </p>
+        </div>
+
+        <div className="grid grid-cols-6 gap-2 mb-3 pb-3 border-b border-gray-800/20 dark:border-white/20">
+          {forecast.map((day, idx) => (
+            <div
+              key={idx}
+              className="flex flex-col items-center bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2"
+            >
+              <p className="text-xs font-medium mb-1">{day.day}</p>
+              <img
+                src={`/weather-ico/${day.icon}`}
+                alt=""
+                className="w-8 h-8 mb-1"
+              />
+              <div className="flex items-center gap-1 text-xs">
+                <span className="font-semibold">{day.high}°</span>
+                <span className="text-gray-600 dark:text-white/60">
+                  {day.low}°
+                </span>
+              </div>
+              {day.precipitation > 0 && (
+                <div className="flex items-center gap-0.5 mt-1">
+                  <Droplets className="w-3 h-3 text-gray-600 dark:text-white/70" />
+                  <span className="text-[10px] text-gray-600 dark:text-white/70">
+                    {day.precipitation}%
+                  </span>
+                </div>
+              )}
+            </div>
+          ))}
+        </div>
+
+        <div className="grid grid-cols-3 gap-2 text-xs">
+          <div className="flex items-center gap-2 bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2">
+            <Wind className="w-4 h-4 text-gray-700 dark:text-white/80 flex-shrink-0" />
+            <div>
+              <p className="text-[10px] text-gray-600 dark:text-white/70">
+                Wind
+              </p>
+              <p className="font-semibold">
+                {Math.round(current.wind_speed_10m)} km/h
+              </p>
+            </div>
+          </div>
+
+          <div className="flex items-center gap-2 bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2">
+            <Droplets className="w-4 h-4 text-gray-700 dark:text-white/80 flex-shrink-0" />
+            <div>
+              <p className="text-[10px] text-gray-600 dark:text-white/70">
+                Humidity
+              </p>
+              <p className="font-semibold">
+                {Math.round(current.relative_humidity_2m)}%
+              </p>
+            </div>
+          </div>
+
+          <div className="flex items-center gap-2 bg-gray-800/10 dark:bg-white/10 backdrop-blur-sm rounded-md p-2">
+            <Gauge className="w-4 h-4 text-gray-700 dark:text-white/80 flex-shrink-0" />
+            <div>
+              <p className="text-[10px] text-gray-600 dark:text-white/70">
+                Feels Like
+              </p>
+              <p className="font-semibold">
+                {Math.round(current.apparent_temperature)}°C
+              </p>
+            </div>
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+};
+
+export default Weather;

src/lib/actions.ts

@@ -1,6 +1,14 @@
 import { Message } from '@/components/ChatWindow';
 
-export const getSuggestions = async (chatHistory: Message[]) => {
+export const getSuggestions = async (chatHistory: [string, string][]) => {
+  const chatTurns = chatHistory.map(([role, content]) => {
+    if (role === 'human') {
+      return { role: 'user', content };
+    } else {
+      return { role: 'assistant', content };
+    }
+  });
+
   const chatModel = localStorage.getItem('chatModelKey');
   const chatModelProvider = localStorage.getItem('chatModelProviderId');
 
@@ -10,7 +18,7 @@ export const getSuggestions = async (chatHistory: Message[]) => {
       'Content-Type': 'application/json',
     },
     body: JSON.stringify({
-      chatHistory: chatHistory,
+      chatHistory: chatTurns,
       chatModel: {
         providerId: chatModelProvider,
         key: chatModel,

src/lib/agents/media/image.ts

@@ -1,21 +1,17 @@
 /* I don't think can be classified as agents but to keep the structure consistent i guess ill keep it here */
 
-import {
-  RunnableSequence,
-  RunnableMap,
-  RunnableLambda,
-} from '@langchain/core/runnables';
-import { ChatPromptTemplate } from '@langchain/core/prompts';
-import formatChatHistoryAsString from '@/lib/utils/formatHistory';
-import { BaseMessage, HumanMessage, SystemMessage } from '@langchain/core/messages';
-import { StringOutputParser } from '@langchain/core/output_parsers';
 import { searchSearxng } from '@/lib/searxng';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import LineOutputParser from '@/lib/outputParsers/lineOutputParser';
-import { imageSearchFewShots, imageSearchPrompt } from '@/lib/prompts/media/image';
+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: BaseMessage[];
+  chatHistory: ChatTurnMessage[];
   query: string;
 };
 
@@ -23,27 +19,32 @@ type ImageSearchResult = {
   img_src: string;
   url: string;
   title: string;
-}
-
-const outputParser = new LineOutputParser({
-  key: 'query',
-})
+};
 
 const searchImages = async (
   input: ImageSearchChainInput,
-  llm: BaseChatModel,
+  llm: BaseLLM<any>,
 ) => {
-  const chatPrompt = await ChatPromptTemplate.fromMessages([
-    new SystemMessage(imageSearchPrompt),
-    ...imageSearchFewShots,
-    new HumanMessage(`<conversation>\n${formatChatHistoryAsString(input.chatHistory)}\n</conversation>\n<follow_up>\n${input.query}\n</follow_up>`)
-  ]).formatMessages({})
+  const schema = z.object({
+    query: z.string().describe('The image search query.'),
+  });
 
-  const res = await llm.invoke(chatPrompt)
+  const res = await llm.generateObject<z.infer<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 query = await outputParser.invoke(res)
-
-  const searchRes = await searchSearxng(query!, {
+  const searchRes = await searchSearxng(res.query, {
     engines: ['bing images', 'google images'],
   });
 

src/lib/agents/media/video.ts

@@ -1,13 +1,15 @@
-import { ChatPromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '@/lib/utils/formatHistory';
-import { BaseMessage, HumanMessage, SystemMessage } from '@langchain/core/messages';
 import { searchSearxng } from '@/lib/searxng';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import LineOutputParser from '@/lib/outputParsers/lineOutputParser';
-import { videoSearchFewShots, videoSearchPrompt } from '@/lib/prompts/media/videos';
+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: BaseMessage[];
+  chatHistory: ChatTurnMessage[];
   query: string;
 };
 
@@ -16,39 +18,39 @@ type VideoSearchResult = {
   url: string;
   title: string;
   iframe_src: string;
-}
-
-const outputParser = new LineOutputParser({
-  key: 'query',
-});
+};
 
 const searchVideos = async (
   input: VideoSearchChainInput,
-  llm: BaseChatModel,
+  llm: BaseLLM<any>,
 ) => {
-  const chatPrompt = await ChatPromptTemplate.fromMessages([
-    new SystemMessage(videoSearchPrompt),
-    ...videoSearchFewShots,
-    new HumanMessage(`<conversation>${formatChatHistoryAsString(input.chatHistory)}\n</conversation>\n<follow_up>\n${input.query}\n</follow_up>`)
-  ]).formatMessages({})
+  const schema = z.object({
+    query: z.string().describe('The video search query.'),
+  });
 
-  const res = await llm.invoke(chatPrompt)
+  const res = await llm.generateObject<z.infer<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 query = await outputParser.invoke(res)
-
-  const searchRes = await searchSearxng(query!, {
+  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
-    ) {
+    if (result.thumbnail && result.url && result.title && result.iframe_src) {
       videos.push({
         img_src: result.thumbnail,
         url: result.url,
@@ -59,7 +61,6 @@ const searchVideos = async (
   });
 
   return videos.slice(0, 10);
-
 };
 
 export default searchVideos;

src/lib/agents/search/classifier/index.ts

@@ -0,0 +1,73 @@
+import z from 'zod';
+import { ClassifierInput, ClassifierOutput } from '../types';
+import { WidgetRegistry } from '../widgets';
+import { IntentRegistry } from './intents';
+import { getClassifierPrompt } from '@/lib/prompts/search/classifier';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+
+class Classifier {
+  async classify(input: ClassifierInput): Promise<ClassifierOutput> {
+    const availableIntents = IntentRegistry.getAvailableIntents({
+      sources: input.enabledSources,
+    });
+
+    const availableWidgets = WidgetRegistry.getAll();
+
+    const classificationSchema = z.object({
+      skipSearch: z
+        .boolean()
+        .describe(
+          'Set to true to SKIP search. Skip ONLY when: (1) widgets alone fully answer the query (e.g., weather, stocks, calculator), (2) simple greetings or writing tasks (NOT questions). Set to false for ANY question or information request.',
+        ),
+      standaloneFollowUp: z
+        .string()
+        .describe(
+          "A self-contained, context-independent reformulation of the user's question. Must include all necessary context from chat history, replace pronouns with specific nouns, and be clear enough to answer without seeing the conversation. Keep the same complexity as the original question.",
+        ),
+      intents: z
+        .array(z.enum(availableIntents.map((i) => i.name)))
+        .describe(
+          "The intent(s) that best describe how to fulfill the user's query. Can include multiple intents (e.g., ['web_search', 'widget_response'] for 'weather in NYC and recent news'). Always include at least one intent when applicable.",
+        ),
+      widgets: z
+        .array(z.union(availableWidgets.map((w) => w.schema)))
+        .describe(
+          'Widgets that can display structured data to answer (fully or partially) the query. Include all applicable widgets regardless of skipSearch value.',
+        ),
+    });
+
+    const classifierPrompt = getClassifierPrompt({
+      intentDesc: IntentRegistry.getDescriptions({
+        sources: input.enabledSources,
+      }),
+      widgetDesc: WidgetRegistry.getDescriptions(),
+    });
+
+    const res = await input.llm.generateObject<
+      z.infer<typeof classificationSchema>
+    >({
+      messages: [
+        {
+          role: 'system',
+          content: classifierPrompt,
+        },
+        {
+          role: 'user',
+          content: `<conversation>${formatChatHistoryAsString(input.chatHistory)}</conversation>\n\n<query>${input.query}</query>`,
+        },
+      ],
+      schema: classificationSchema,
+    });
+
+    res.widgets = res.widgets.map((widgetConfig) => {
+      return {
+        type: widgetConfig.type,
+        params: widgetConfig,
+      };
+    });
+
+    return res as ClassifierOutput;
+  }
+}
+
+export default Classifier;

src/lib/agents/search/classifier/intents/academicSearch.ts

@@ -0,0 +1,52 @@
+import { Intent } from '../../types';
+
+const description = `Use this intent to search for scholarly articles, research papers, scientific studies, and academic resources when the user explicitly requests credible, peer-reviewed, or authoritative information from academic sources.
+
+#### When to use:
+1. User explicitly mentions academic keywords: research papers, scientific studies, scholarly articles, peer-reviewed, journal articles.
+2. User asks for scientific evidence or academic research on a topic.
+3. User needs authoritative, citation-worthy sources for research or academic purposes.
+
+#### When NOT to use:
+1. General questions that don't specifically request academic sources - use 'web_search' instead.
+2. User just wants general information without specifying academic sources.
+3. Casual queries about facts or current events.
+
+#### Example use cases:
+1. "Find scientific papers on climate change effects"
+   - User explicitly wants scientific papers.
+   - Intent: ['academic_search'] with skipSearch: false
+
+2. "What does the research say about meditation benefits?"
+   - User is asking for research-based information.
+   - Intent: ['academic_search', 'web_search'] with skipSearch: false
+
+3. "Show me peer-reviewed articles on CRISPR technology"
+   - User specifically wants peer-reviewed academic content.
+   - Intent: ['academic_search'] with skipSearch: false
+
+4. "I need scholarly sources about renewable energy for my thesis"
+   - User explicitly needs scholarly/academic sources.
+   - Intent: ['academic_search'] with skipSearch: false
+
+5. "Explain quantum computing" (WRONG to use academic_search alone)
+   - This is a general question, not specifically requesting academic papers.
+   - Correct intent: ['web_search'] with skipSearch: false
+   - Could combine: ['web_search', 'academic_search'] if you want both general and academic sources
+
+6. "What's the latest study on sleep patterns?"
+   - User mentions "study" - combine academic and web search for comprehensive results.
+   - Intent: ['academic_search', 'web_search'] with skipSearch: false
+
+**IMPORTANT**: This intent can be combined with 'web_search' to provide both academic papers and general web information. Always set skipSearch to false when using this intent.
+
+**NOTE**: This intent is only available if academic search sources are enabled in the configuration.`;
+
+const academicSearchIntent: Intent = {
+  name: 'academic_search',
+  description,
+  requiresSearch: true,
+  enabled: (config) => config.sources.includes('academic'),
+};
+
+export default academicSearchIntent;

src/lib/agents/search/classifier/intents/discussionSearch.ts

@@ -0,0 +1,55 @@
+import { Intent } from '../../types';
+
+const description = `Use this intent to search through discussion forums, community boards, and social platforms (Reddit, forums, etc.) when the user explicitly wants opinions, personal experiences, community discussions, or crowd-sourced information.
+
+#### When to use:
+1. User explicitly mentions: Reddit, forums, discussion boards, community opinions, "what do people think", "user experiences".
+2. User is asking for opinions, reviews, or personal experiences about a product, service, or topic.
+3. User wants to know what communities or people are saying about something.
+
+#### When NOT to use:
+1. General questions that don't specifically ask for opinions or discussions - use 'web_search' instead.
+2. User wants factual information or official sources.
+3. Casual queries about facts, news, or current events without requesting community input.
+
+#### Example use cases:
+1. "What do people on Reddit think about the new iPhone?"
+   - User explicitly wants Reddit/community opinions.
+   - Intent: ['discussions_search'] with skipSearch: false
+
+2. "User experiences with Tesla Model 3"
+   - User is asking for personal experiences from users.
+   - Intent: ['discussions_search'] with skipSearch: false
+
+3. "Best gaming laptop according to forums"
+   - User wants forum/community recommendations.
+   - Intent: ['discussions_search'] with skipSearch: false
+
+4. "What are people saying about the new AI regulations?"
+   - User wants community discussions/opinions.
+   - Intent: ['discussions_search', 'web_search'] with skipSearch: false
+
+5. "Reviews and user opinions on the Framework laptop"
+   - Combines user opinions with general reviews.
+   - Intent: ['discussions_search', 'web_search'] with skipSearch: false
+
+6. "What's the price of iPhone 15?" (WRONG to use discussions_search)
+   - This is a factual question, not asking for opinions.
+   - Correct intent: ['web_search'] with skipSearch: false
+
+7. "Explain how OAuth works" (WRONG to use discussions_search)
+   - This is asking for information, not community opinions.
+   - Correct intent: ['web_search'] with skipSearch: false
+
+**IMPORTANT**: This intent can be combined with 'web_search' to provide both community discussions and official/factual information. Always set skipSearch to false when using this intent.
+
+**NOTE**: This intent is only available if discussion search sources are enabled in the configuration.`;
+
+const discussionSearchIntent: Intent = {
+  name: 'discussions_search',
+  description,
+  requiresSearch: true,
+  enabled: (config) => config.sources.includes('discussions'),
+};
+
+export default discussionSearchIntent;

src/lib/agents/search/classifier/intents/index.ts

@@ -0,0 +1,16 @@
+import academicSearchIntent from './academicSearch';
+import discussionSearchIntent from './discussionSearch';
+import privateSearchIntent from './privateSearch';
+import IntentRegistry from './registry';
+import webSearchIntent from './webSearch';
+import widgetResponseIntent from './widgetResponse';
+import writingTaskIntent from './writingTask';
+
+IntentRegistry.register(webSearchIntent);
+IntentRegistry.register(academicSearchIntent);
+IntentRegistry.register(discussionSearchIntent);
+IntentRegistry.register(widgetResponseIntent);
+IntentRegistry.register(writingTaskIntent);
+IntentRegistry.register(privateSearchIntent);
+
+export { IntentRegistry };

src/lib/agents/search/classifier/intents/privateSearch.ts

@@ -0,0 +1,47 @@
+import { Intent } from '../../types';
+
+const description = `Use this intent to search through the user's uploaded documents or provided web page links when they ask questions about their personal files or specific URLs.
+
+#### When to use:
+1. User explicitly asks about uploaded documents ("tell me about the document I uploaded", "summarize this file").
+2. User provides specific URLs/links and asks questions about them ("tell me about example.com", "what's on this page: url.com").
+3. User references "my documents", "the file I shared", "this link" when files or URLs are available.
+
+#### When NOT to use:
+1. User asks generic questions like "summarize" without providing context or files (later the system will ask what they want summarized).
+2. No files have been uploaded and no URLs provided - use web_search or other intents instead.
+3. User is asking general questions unrelated to their uploaded content.
+
+#### Example use cases:
+1. "Tell me about the PDF I uploaded"
+   - Files are uploaded, user wants information from them.
+   - Intent: ['private_search'] with skipSearch: false
+
+2. "What's the main point from example.com?"
+   - User provided a specific URL to analyze.
+   - Intent: ['private_search'] with skipSearch: false
+
+3. "Summarize the research paper I shared"
+   - User references a shared document.
+   - Intent: ['private_search'] with skipSearch: false
+
+4. "Summarize" (WRONG to use private_search if no files/URLs)
+   - No context provided, no files uploaded.
+   - Correct: Skip this intent, let the answer agent ask what to summarize
+
+5. "What does my document say about climate change and also search the web for recent updates?"
+   - Combine private document search with web search.
+   - Intent: ['private_search', 'web_search'] with skipSearch: false
+
+**IMPORTANT**: Only use this intent if files are actually uploaded or URLs are explicitly provided in the query. Check the context for uploaded files before selecting this intent. Always set skipSearch to false when using this intent.
+
+**NOTE**: This intent can be combined with other search intents when the user wants both personal document information and external sources.`;
+
+const privateSearchIntent: Intent = {
+  name: 'private_search',
+  description,
+  enabled: (config) => true,
+  requiresSearch: true,
+};
+
+export default privateSearchIntent;

src/lib/agents/search/classifier/intents/registry.ts

@@ -0,0 +1,31 @@
+import { Intent, SearchAgentConfig, SearchSources } from '../../types';
+
+class IntentRegistry {
+  private static intents = new Map<string, Intent>();
+
+  static register(intent: Intent) {
+    this.intents.set(intent.name, intent);
+  }
+
+  static get(name: string): Intent | undefined {
+    return this.intents.get(name);
+  }
+
+  static getAvailableIntents(config: { sources: SearchSources[] }): Intent[] {
+    return Array.from(
+      this.intents.values().filter((intent) => intent.enabled(config)),
+    );
+  }
+
+  static getDescriptions(config: { sources: SearchSources[] }): string {
+    const availableintents = this.getAvailableIntents(config);
+
+    return availableintents
+      .map(
+        (intent) => `-------\n\n###${intent.name}: ${intent.description}\n\n`,
+      )
+      .join('\n\n');
+  }
+}
+
+export default IntentRegistry;

src/lib/agents/search/classifier/intents/webSearch.ts

@@ -0,0 +1,31 @@
+import { Intent } from '../../types';
+
+const description = `
+Use this intent to find current information from the web when the user is asking a question or needs up-to-date information that cannot be provided by widgets or other intents. 
+
+#### When to use:
+1. Simple user questions about current events, news, weather, or general knowledge that require the latest information and there is no specific better intent to use.
+2. When the user explicitly requests information from the web or indicates they want the most recent data (and still there's no other better intent).
+3. When no widgets can fully satisfy the user's request for information nor any other specialized search intent applies.
+
+#### Examples use cases:
+1. "What is the weather in San Francisco today? ALso tell me some popular events happening there this weekend."
+    - In this case, the weather widget can provide the current weather, but for popular events, a web search is needed. So the intent should include a 'web_search' & a 'widget_response'.
+
+2. "Who won the Oscar for Best Picture in 2024?"
+    - This is a straightforward question that requires current information from the web.
+
+3. "Give me the latest news on AI regulations."
+    - The user is asking for up-to-date news, which necessitates a web search.
+
+**IMPORTANT**: If this intent is given then skip search should be false.
+`;
+
+const webSearchIntent: Intent = {
+  name: 'web_search',
+  description: description,
+  requiresSearch: true,
+  enabled: (config) => config.sources.includes('web'),
+};
+
+export default webSearchIntent;

src/lib/agents/search/classifier/intents/widgetResponse.ts

@@ -0,0 +1,47 @@
+import { Intent } from '../../types';
+
+const description = `Use this intent when the user's query can be fully or partially answered using specialized widgets that provide structured, real-time data (weather, stocks, calculations, and more).
+
+#### When to use:
+1. The user is asking for specific information that a widget can provide (current weather, stock prices, mathematical calculations, unit conversions, etc.).
+2. A widget can completely answer the query without needing additional web search (use this intent alone and set skipSearch to true).
+3. A widget can provide part of the answer, but additional information from web search or other sources is needed (combine with other intents like 'web_search' and set skipSearch to false).
+
+#### Example use cases:
+Note: These are just examples - there are several other widgets available for use depending on the user's query.
+
+1. "What is the weather in New York?"
+   - The weather widget can fully answer this query.
+   - Intent: ['widget_response'] with skipSearch: true
+   - Widget: [{ type: 'weather', location: 'New York', lat: 0, lon: 0 }]
+
+2. "What's the weather in San Francisco today? Also tell me some popular events happening there this weekend."
+   - Weather widget provides current conditions, but events require web search.
+   - Intent: ['web_search', 'widget_response'] with skipSearch: false
+   - Widget: [{ type: 'weather', location: 'San Francisco', lat: 0, lon: 0 }]
+
+3. "Calculate 25% of 480"
+   - The calculator widget can fully answer this.
+   - Intent: ['widget_response'] with skipSearch: true
+    - Widget: [{ type: 'calculator', expression: '25% of 480' }] 
+
+4. "AAPL stock price and recent Apple news"
+   - Stock widget provides price, but news requires web search.
+   - Intent: ['web_search', 'widget_response'] with skipSearch: false
+    - Widget: [{ type: 'stock', symbol: 'AAPL' }]
+
+5. "What's Tesla's stock doing and how does it compare to competitors?"
+   - Stock widget provides Tesla's price, but comparison analysis requires web search.
+   - Intent: ['web_search', 'widget_response'] with skipSearch: false
+  - Widget: [{ type: 'stock', symbol: 'TSLA' }]
+
+**IMPORTANT**: Set skipSearch to true ONLY if the widget(s) can completely answer the user's query without any additional information. If the user asks for anything beyond what the widget provides (context, explanations, comparisons, related information), combine this intent with 'web_search' and set skipSearch to false.`;
+
+const widgetResponseIntent: Intent = {
+  name: 'widget_response',
+  description,
+  requiresSearch: false,
+  enabled: (config) => true,
+};
+
+export default widgetResponseIntent;

src/lib/agents/search/classifier/intents/writingTask.ts

@@ -0,0 +1,53 @@
+import { Intent } from '../../types';
+
+const description = `Use this intent for simple writing or greeting tasks that do not require any external information or facts. This is ONLY for greetings and straightforward creative writing that needs no factual verification.
+
+#### When to use:
+1. User greetings or simple social interactions (hello, hi, thanks, goodbye).
+2. Creative writing tasks that require NO factual information (poems, birthday messages, thank you notes).
+3. Simple drafting tasks where the user provides all necessary information.
+
+#### When NOT to use:
+1. ANY question that starts with "what", "how", "why", "when", "where", "who" - these need web_search.
+2. Requests for explanations, definitions, or information about anything.
+3. Code-related questions or technical help - these need web_search.
+4. Writing tasks that require facts, data, or current information.
+5. When you're uncertain about any information needed - default to web_search.
+
+#### Example use cases:
+1. "Hello" or "Hi there"
+   - Simple greeting, no information needed.
+   - Intent: ['writing_task'] with skipSearch: true
+
+2. "Write me a birthday message for my friend"
+   - Creative writing, no facts needed.
+   - Intent: ['writing_task'] with skipSearch: true
+
+3. "Draft a thank you email for a job interview"
+   - Simple writing task, no external information required.
+   - Intent: ['writing_task'] with skipSearch: true
+
+4. "What is React?" (WRONG to use writing_task)
+   - This is a QUESTION asking for information.
+   - Correct intent: ['web_search'] with skipSearch: false
+
+5. "How do I fix this error in Python?" (WRONG to use writing_task)
+   - This is asking for technical help.
+   - Correct intent: ['web_search'] with skipSearch: false
+
+6. "Write an email about the latest AI developments" (WRONG to use writing_task alone)
+   - This requires current information about AI developments.
+   - Correct intent: ['web_search'] with skipSearch: false
+
+**CRITICAL RULE**: When in doubt, DO NOT use this intent. Default to web_search. This intent should be rare - only use it for greetings and purely creative writing tasks that need absolutely no facts or information.
+
+**IMPORTANT**: If this intent is used alone, skipSearch should be true. Never combine this with other search intents unless you're absolutely certain both are needed.`;
+
+const writingTaskIntent: Intent = {
+  name: 'writing_task',
+  description,
+  requiresSearch: false,
+  enabled: (config) => true,
+};
+
+export default writingTaskIntent;

src/lib/agents/search/index.ts

@@ -0,0 +1,105 @@
+import { ResearcherOutput, SearchAgentInput } from './types';
+import SessionManager from '@/lib/session';
+import Classifier from './classifier';
+import { WidgetRegistry } from './widgets';
+import Researcher from './researcher';
+import { getWriterPrompt } from '@/lib/prompts/search/writer';
+import fs from 'fs';
+
+class SearchAgent {
+  async searchAsync(session: SessionManager, input: SearchAgentInput) {
+    const classifier = new Classifier();
+
+    const classification = await classifier.classify({
+      chatHistory: input.chatHistory,
+      enabledSources: input.config.sources,
+      query: input.followUp,
+      llm: input.config.llm,
+    });
+
+    const widgetPromise = WidgetRegistry.executeAll(classification.widgets, {
+      llm: input.config.llm,
+      embedding: input.config.embedding,
+      session: session,
+    }).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.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?.findings
+        .filter((f) => f.type === 'search_results')
+        .flatMap((f) => f.results)
+        .map((f) => `${f.metadata.title}: ${f.content}`)
+        .join('\n') || '';
+
+    const widgetContext = widgetOutputs
+      .map((o) => {
+        return `${o.type}: ${JSON.stringify(o.data)}`;
+      })
+      .join('\n-------------\n');
+
+    const finalContextWithWidgets = `<search_results note="These are the search results and you can cite these">${finalContext}</search_results>\n<widgets_result noteForAssistant="Its output is already showed to the user, you can use this information to answer the query but do not CITE this as a souce">${widgetContext}</widgets_result>`;
+
+    const writerPrompt = getWriterPrompt(finalContextWithWidgets);
+
+    const answerStream = input.config.llm.streamText({
+      messages: [
+        {
+          role: 'system',
+          content: writerPrompt,
+        },
+        ...input.chatHistory,
+        {
+          role: 'user',
+          content: input.followUp,
+        },
+      ],
+    });
+
+    let accumulatedText = '';
+
+    for await (const chunk of answerStream) {
+      accumulatedText += chunk.contentChunk;
+
+      session.emit('data', {
+        type: 'response',
+        data: chunk.contentChunk,
+      });
+    }
+
+    session.emit('end', {});
+  }
+}
+
+export default SearchAgent;

src/lib/agents/search/researcher/actions/done.ts

@@ -0,0 +1,19 @@
+import z from 'zod';
+import { ResearchAction } from '../../types';
+
+const doneAction: ResearchAction<any> = {
+  name: 'done',
+  description:
+    "Indicates that the research process is complete and no further actions are needed. Use this action when you have gathered sufficient information to answer the user's query.",
+  enabled: (_) => true,
+  schema: z.object({
+    type: z.literal('done'),
+  }),
+  execute: async (params, additionalConfig) => {
+    return {
+      type: 'done',
+    };
+  },
+};
+
+export default doneAction;

src/lib/agents/search/researcher/actions/index.ts

@@ -0,0 +1,8 @@
+import doneAction from './done';
+import ActionRegistry from './registry';
+import webSearchAction from './webSearch';
+
+ActionRegistry.register(webSearchAction);
+ActionRegistry.register(doneAction);
+
+export { ActionRegistry };

src/lib/agents/search/researcher/actions/registry.ts

@@ -0,0 +1,73 @@
+import {
+  ActionConfig,
+  ActionOutput,
+  AdditionalConfig,
+  ClassifierOutput,
+  ResearchAction,
+} from '../../types';
+
+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;
+  }): ResearchAction[] {
+    return Array.from(
+      this.actions.values().filter((action) => action.enabled(config)),
+    );
+  }
+
+  static getAvailableActionsDescriptions(config: {
+    classification: ClassifierOutput;
+  }): string {
+    const availableActions = this.getAvailableActions(config);
+
+    return availableActions
+      .map((action) => `------------\n##${action.name}\n${action.description}`)
+      .join('\n\n');
+  }
+
+  static async execute(
+    name: string,
+    params: any,
+    additionalConfig: AdditionalConfig,
+  ) {
+    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: ActionConfig[],
+    additionalConfig: AdditionalConfig,
+  ): Promise<ActionOutput[]> {
+    const results: ActionOutput[] = [];
+
+    await Promise.all(
+      actions.map(async (actionConfig) => {
+        const output = await this.execute(
+          actionConfig.type,
+          actionConfig.params,
+          additionalConfig,
+        );
+        results.push(output);
+      }),
+    );
+
+    return results;
+  }
+}
+
+export default ActionRegistry;

src/lib/agents/search/researcher/actions/webSearch.ts

@@ -0,0 +1,56 @@
+import z from 'zod';
+import { ResearchAction } from '../../types';
+import { searchSearxng } from '@/lib/searxng';
+import { Chunk } from '@/lib/types';
+
+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 actionDescription = `
+You have to use this action aggressively to find relevant information from the web to answer user queries. You can combine this action with other actions to gather comprehensive data. Always ensure that you provide accurate and up-to-date information by leveraging web search results.
+When this action is present, you must use it to obtain current information from the web. 
+
+### How to use:
+1. For speed search mode, you can use this action once. Make sure to cover all aspects of the user's query in that single search.
+2. If you're on quality mode, you'll get to use this action up to two times. Use the first search to gather general information, and the second search to fill in any gaps or get more specific details based on the initial findings.
+3. If you're set on quality mode, then you will get to use this action multiple times to gather more information. Use your judgment to decide when additional searches are necessary to provide a thorough and accurate response.
+
+Input: An array of search queries. Make sure the queries are relevant to the user's request and cover different aspects if necessary. You can include a maximum of 3 queries. Make sure the queries are SEO friendly and not sentences rather keywords which can be used to search a search engine like Google, Bing, etc.
+`;
+
+const webSearchAction: ResearchAction<typeof actionSchema> = {
+  name: 'web_search',
+  description: actionDescription,
+  schema: actionSchema,
+  enabled: (config) => config.classification.intents.includes('web_search'),
+  execute: async (input, _) => {
+    let results: Chunk[] = [];
+
+    const search = async (q: string) => {
+      const res = await searchSearxng(q);
+
+      res.results.forEach((r) => {
+        results.push({
+          content: r.content || r.title,
+          metadata: {
+            title: r.title,
+            url: r.url,
+          },
+        });
+      });
+    };
+
+    await Promise.all(input.queries.map(search));
+
+    return {
+      type: 'search_results',
+      results,
+    };
+  },
+};
+
+export default webSearchAction;

src/lib/agents/search/researcher/index.ts

@@ -0,0 +1,231 @@
+import z from 'zod';
+import {
+  ActionConfig,
+  ActionOutput,
+  ResearcherInput,
+  ResearcherOutput,
+} from '../types';
+import { ActionRegistry } from './actions';
+import { getResearcherPrompt } from '@/lib/prompts/search/researcher';
+import SessionManager from '@/lib/session';
+import { ReasoningResearchBlock } from '@/lib/types';
+import formatChatHistoryAsString from '@/lib/utils/formatHistory';
+
+class Researcher {
+  async research(
+    session: SessionManager,
+    input: ResearcherInput,
+  ): Promise<ResearcherOutput> {
+    let findings: string = '';
+    let actionOutput: ActionOutput[] = [];
+    let maxIteration =
+      input.config.mode === 'speed'
+        ? 1
+        : input.config.mode === 'balanced'
+          ? 3
+          : 25;
+
+    const availableActions = ActionRegistry.getAvailableActions({
+      classification: input.classification,
+    });
+
+    const schema = z.object({
+      reasoning: z
+        .string()
+        .describe('The reasoning behind choosing the next action.'),
+      action: z
+        .union(availableActions.map((a) => a.schema))
+        .describe('The action to be performed next.'),
+    });
+
+    const availableActionsDescription =
+      ActionRegistry.getAvailableActionsDescriptions({
+        classification: input.classification,
+      });
+
+    const researchBlockId = crypto.randomUUID();
+
+    session.emitBlock({
+      id: researchBlockId,
+      type: 'research',
+      data: {
+        subSteps: [],
+      },
+    });
+
+    for (let i = 0; i < maxIteration; i++) {
+      const researcherPrompt = getResearcherPrompt(
+        availableActionsDescription,
+        input.config.mode,
+        i,
+        maxIteration,
+      );
+
+      const actionStream = input.config.llm.streamObject<
+        z.infer<typeof schema>
+      >({
+        messages: [
+          {
+            role: 'system',
+            content: researcherPrompt,
+          },
+          {
+            role: 'user',
+            content: `
+                    <conversation>
+                    ${formatChatHistoryAsString(input.chatHistory.slice(-10))}
+                    User: ${input.followUp} (Standalone question: ${input.classification.standaloneFollowUp})
+                    </conversation>
+
+                    <previous_actions>
+                    ${findings}
+                    </previous_actions>
+                    `,
+          },
+        ],
+        schema,
+      });
+
+      const block = session.getBlock(researchBlockId);
+
+      let reasoningEmitted = false;
+      let reasoningId = crypto.randomUUID();
+
+      let finalActionRes: any;
+
+      for await (const partialRes of actionStream) {
+        try {
+          if (
+            partialRes.reasoning &&
+            !reasoningEmitted &&
+            block &&
+            block.type === 'research'
+          ) {
+            reasoningEmitted = true;
+            block.data.subSteps.push({
+              id: reasoningId,
+              type: 'reasoning',
+              reasoning: partialRes.reasoning,
+            });
+            session.updateBlock(researchBlockId, [
+              {
+                op: 'replace',
+                path: '/data/subSteps',
+                value: block.data.subSteps,
+              },
+            ]);
+          } else if (
+            partialRes.reasoning &&
+            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 = partialRes.reasoning;
+              session.updateBlock(researchBlockId, [
+                {
+                  op: 'replace',
+                  path: '/data/subSteps',
+                  value: block.data.subSteps,
+                },
+              ]);
+            }
+          }
+
+          finalActionRes = partialRes;
+        } catch (e) {
+          // nothing
+        }
+      }
+
+      if (finalActionRes.action.type === 'done') {
+        break;
+      }
+
+      const actionConfig: ActionConfig = {
+        type: finalActionRes.action.type as string,
+        params: finalActionRes.action,
+      };
+
+      const queries = actionConfig.params.queries || [];
+      if (block && block.type === 'research') {
+        block.data.subSteps.push({
+          id: crypto.randomUUID(),
+          type: 'searching',
+          searching: queries,
+        });
+        session.updateBlock(researchBlockId, [
+          { op: 'replace', path: '/data/subSteps', value: block.data.subSteps },
+        ]);
+      }
+
+      findings += `\n---\nIteration ${i + 1}:\n`;
+      findings += 'Reasoning: ' + finalActionRes.reasoning + '\n';
+      findings += `Executing Action: ${actionConfig.type} with params ${JSON.stringify(actionConfig.params)}\n`;
+
+      const actionResult = await ActionRegistry.execute(
+        actionConfig.type,
+        actionConfig.params,
+        {
+          llm: input.config.llm,
+          embedding: input.config.embedding,
+          session: session,
+        },
+      );
+
+      actionOutput.push(actionResult);
+
+      if (actionResult.type === 'search_results') {
+        if (block && block.type === 'research') {
+          block.data.subSteps.push({
+            id: crypto.randomUUID(),
+            type: 'reading',
+            reading: actionResult.results,
+          });
+          session.updateBlock(researchBlockId, [
+            {
+              op: 'replace',
+              path: '/data/subSteps',
+              value: block.data.subSteps,
+            },
+          ]);
+        }
+
+        findings += actionResult.results
+          .map(
+            (r) =>
+              `Title: ${r.metadata.title}\nURL: ${r.metadata.url}\nContent: ${r.content}\n`,
+          )
+          .join('\n');
+      }
+
+      findings += '\n---------\n';
+    }
+
+    const searchResults = actionOutput.filter(
+      (a) => a.type === 'search_results',
+    );
+
+    session.emit('data', {
+      type: 'sources',
+      data: searchResults
+        .flatMap((a) => a.results)
+        .map((r) => ({
+          content: r.content,
+          metadata: r.metadata,
+        })),
+    });
+
+    return {
+      findings: actionOutput,
+    };
+  }
+}
+
+export default Researcher;

src/lib/agents/search/types.ts

@@ -0,0 +1,107 @@
+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[];
+  llm: BaseLLM<any>;
+  embedding: BaseEmbedding<any>;
+  mode: 'speed' | 'balanced' | 'quality';
+};
+
+export type SearchAgentInput = {
+  chatHistory: ChatTurnMessage[];
+  followUp: string;
+  config: SearchAgentConfig;
+};
+
+export interface Intent {
+  name: string;
+  description: string;
+  requiresSearch: boolean;
+  enabled: (config: { sources: SearchSources[] }) => boolean;
+}
+
+export type Widget<TSchema extends z.ZodObject<any> = z.ZodObject<any>> = {
+  name: string;
+  description: string;
+  schema: TSchema;
+  execute: (
+    params: z.infer<TSchema>,
+    additionalConfig: AdditionalConfig,
+  ) => Promise<WidgetOutput>;
+};
+
+export type WidgetConfig = {
+  type: string;
+  params: Record<string, any>;
+};
+
+export type WidgetOutput = {
+  type: string;
+  data: any;
+};
+
+export type ClassifierInput = {
+  llm: BaseLLM<any>;
+  enabledSources: SearchSources[];
+  query: string;
+  chatHistory: ChatTurnMessage[];
+};
+
+export type ClassifierOutput = {
+  skipSearch: boolean;
+  standaloneFollowUp: string;
+  intents: string[];
+  widgets: WidgetConfig[];
+};
+
+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[];
+};
+
+export type SearchActionOutput = {
+  type: 'search_results';
+  results: Chunk[];
+};
+
+export type DoneActionOutput = {
+  type: 'done';
+};
+
+export type ActionOutput = SearchActionOutput | DoneActionOutput;
+
+export interface ResearchAction<
+  TSchema extends z.ZodObject<any> = z.ZodObject<any>,
+> {
+  name: string;
+  description: string;
+  schema: z.ZodObject<any>;
+  enabled: (config: { classification: ClassifierOutput }) => boolean;
+  execute: (
+    params: z.infer<TSchema>,
+    additionalConfig: AdditionalConfig,
+  ) => Promise<ActionOutput>;
+}
+
+export type ActionConfig = {
+  type: string;
+  params: Record<string, any>;
+};

src/lib/agents/search/widgets/calculationWidget.ts

@@ -0,0 +1,65 @@
+import z from 'zod';
+import { Widget } from '../types';
+import { evaluate as mathEval } from 'mathjs';
+
+const schema = z.object({
+  type: z.literal('calculation'),
+  expression: z
+    .string()
+    .describe(
+      "A valid mathematical expression to be evaluated (e.g., '2 + 2', '3 * (4 + 5)').",
+    ),
+});
+
+const calculationWidget: Widget<typeof schema> = {
+  name: 'calculation',
+  description: `Performs mathematical calculations and evaluates mathematical expressions. Supports arithmetic operations, algebraic equations, functions, and complex mathematical computations.
+
+**What it provides:**
+- Evaluates mathematical expressions and returns computed results
+- Handles basic arithmetic (+, -, *, /)
+- Supports functions (sqrt, sin, cos, log, etc.)
+- Can process complex expressions with parentheses and order of operations
+
+**When to use:**
+- User asks to calculate, compute, or evaluate a mathematical expression
+- Questions like "what is X", "calculate Y", "how much is Z" where X/Y/Z are math expressions
+- Any request involving numbers and mathematical operations
+
+**Example call:**
+{
+  "type": "calculation",
+  "expression": "25% of 480"
+}
+
+{
+  "type": "calculation", 
+  "expression": "sqrt(144) + 5 * 2"
+}
+
+**Important:** The expression must be valid mathematical syntax that can be evaluated by mathjs. Format percentages as "0.25 * 480" or "25% of 480". Do not include currency symbols, units, or non-mathematical text in the expression.`,
+  schema: schema,
+  execute: async (params, _) => {
+    try {
+      const result = mathEval(params.expression);
+
+      return {
+        type: 'calculation_result',
+        data: {
+          expression: params.expression,
+          result: result,
+        },
+      };
+    } catch (error) {
+      return {
+        type: 'calculation_result',
+        data: {
+          expression: params.expression,
+          result: `Error evaluating expression: ${error}`,
+        },
+      };
+    }
+  },
+};
+
+export default calculationWidget;

src/lib/agents/search/widgets/index.ts

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

src/lib/agents/search/widgets/registry.ts

@@ -0,0 +1,65 @@
+import {
+  AdditionalConfig,
+  SearchAgentConfig,
+  Widget,
+  WidgetConfig,
+  WidgetOutput,
+} from '../types';
+
+class WidgetRegistry {
+  private static widgets = new Map<string, Widget>();
+
+  static register(widget: Widget<any>) {
+    this.widgets.set(widget.name, widget);
+  }
+
+  static get(name: string): Widget | undefined {
+    return this.widgets.get(name);
+  }
+
+  static getAll(): Widget[] {
+    return Array.from(this.widgets.values());
+  }
+
+  static getDescriptions(): string {
+    return Array.from(this.widgets.values())
+      .map((widget) => `${widget.name}: ${widget.description}`)
+      .join('\n\n');
+  }
+
+  static async execute(
+    name: string,
+    params: any,
+    config: AdditionalConfig,
+  ): Promise<WidgetOutput> {
+    const widget = this.get(name);
+
+    if (!widget) {
+      throw new Error(`Widget with name ${name} not found`);
+    }
+
+    return widget.execute(params, config);
+  }
+
+  static async executeAll(
+    widgets: WidgetConfig[],
+    additionalConfig: AdditionalConfig,
+  ): Promise<WidgetOutput[]> {
+    const results: WidgetOutput[] = [];
+
+    await Promise.all(
+      widgets.map(async (widgetConfig) => {
+        const output = await this.execute(
+          widgetConfig.type,
+          widgetConfig.params,
+          additionalConfig,
+        );
+        results.push(output);
+      }),
+    );
+
+    return results;
+  }
+}
+
+export default WidgetRegistry;

src/lib/agents/search/widgets/stockWidget.ts

@@ -0,0 +1,412 @@
+import z from 'zod';
+import { Widget } from '../types';
+import YahooFinance from 'yahoo-finance2';
+
+const yf = new YahooFinance({
+  suppressNotices: ['yahooSurvey'],
+});
+
+const schema = z.object({
+  type: z.literal('stock'),
+  ticker: z
+    .string()
+    .describe(
+      "The stock ticker symbol in uppercase (e.g., 'AAPL' for Apple Inc., 'TSLA' for Tesla, 'GOOGL' for Google). Use the primary exchange ticker.",
+    ),
+  comparisonTickers: z
+    .array(z.string())
+    .max(3)
+    .describe(
+      "Optional array of up to 3 ticker symbols to compare against the base ticker (e.g., ['MSFT', 'GOOGL', 'META']). Charts will show percentage change comparison.",
+    ),
+});
+
+const stockWidget: Widget<typeof schema> = {
+  name: 'stock',
+  description: `Provides comprehensive real-time stock market data and financial information for any publicly traded company. Returns detailed quote data, market status, trading metrics, and company fundamentals.
+
+You can set skipSearch to true if the stock widget can fully answer the user's query without needing additional web search.
+
+**What it provides:**
+- **Real-time Price Data**: Current price, previous close, open price, day's range (high/low)
+- **Market Status**: Whether market is currently open or closed, trading sessions
+- **Trading Metrics**: Volume, average volume, bid/ask prices and sizes
+- **Performance**: Price changes (absolute and percentage), 52-week high/low range
+- **Valuation**: Market capitalization, P/E ratio, earnings per share (EPS)
+- **Dividends**: Dividend rate, dividend yield, ex-dividend date
+- **Company Info**: Full company name, exchange, currency, sector/industry (when available)
+- **Advanced Metrics**: Beta, trailing/forward P/E, book value, price-to-book ratio
+- **Charts Data**: Historical price movements for visualization
+- **Comparison**: Compare up to 3 stocks side-by-side with percentage-based performance visualization
+
+**When to use:**
+- User asks about a stock price ("What's AAPL stock price?", "How is Tesla doing?")
+- Questions about company market performance ("Is Microsoft up or down today?")
+- Requests for stock market data, trading info, or company valuation
+- Queries about dividends, P/E ratio, market cap, or other financial metrics
+- Any stock/equity-related question for a specific company
+- Stock comparisons ("Compare AAPL vs MSFT", "How is TSLA doing vs RIVN and LCID?")
+
+**Example calls:**
+{
+  "type": "stock",
+  "ticker": "AAPL"
+}
+
+{
+  "type": "stock",
+  "ticker": "TSLA",
+  "comparisonTickers": ["RIVN", "LCID"]
+}
+
+{
+  "type": "stock",
+  "ticker": "GOOGL",
+  "comparisonTickers": ["MSFT", "META", "AMZN"]
+}
+
+**Important:** 
+- Use the correct ticker symbol (uppercase preferred: AAPL not aapl)
+- For companies with multiple share classes, use the most common one (e.g., GOOGL for Google Class A shares)
+- The widget works for stocks listed on major exchanges (NYSE, NASDAQ, etc.)
+- Returns comprehensive data; the UI will display relevant metrics based on availability
+- Market data may be delayed by 15-20 minutes for free data sources during trading hours`,
+  schema: schema,
+  execute: async (params, _) => {
+    try {
+      const ticker = params.ticker.toUpperCase();
+
+      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.comparisonTickers.length > 0) {
+        const comparisonPromises = params.comparisonTickers
+          .slice(0, 3)
+          .map(async (compTicker) => {
+            try {
+              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 ${compTicker}:`,
+                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',
+        data: stockData,
+      };
+    } catch (error: any) {
+      return {
+        type: 'stock',
+        data: {
+          error: `Error fetching stock data: ${error.message || error}`,
+          ticker: params.ticker,
+        },
+      };
+    }
+  },
+};
+
+export default stockWidget;

src/lib/agents/search/widgets/weatherWidget.ts

@@ -0,0 +1,174 @@
+import z from 'zod';
+import { Widget } from '../types';
+
+const WeatherWidgetSchema = z.object({
+  type: z.literal('weather'),
+  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.',
+    ),
+});
+
+const weatherWidget: Widget<typeof WeatherWidgetSchema> = {
+  name: 'weather',
+  description: `Provides comprehensive current weather information and forecasts for any location worldwide. Returns real-time weather data including temperature, conditions, humidity, wind, and multi-day forecasts.
+
+You can set skipSearch to true if the weather widget can fully answer the user's query without needing additional web search.
+
+**What it provides:**
+- Current weather conditions (temperature, feels-like, humidity, precipitation)
+- Wind speed, direction, and gusts
+- Weather codes/conditions (clear, cloudy, rainy, etc.)
+- Hourly forecast for next 24 hours
+- Daily forecast for next 7 days (high/low temps, precipitation probability)
+- Timezone information
+
+**When to use:**
+- User asks about weather in a location ("weather in X", "is it raining in Y")
+- Questions about temperature, conditions, or forecast
+- Any weather-related query for a specific place
+
+**Example call:**
+{
+  "type": "weather",
+  "location": "San Francisco, CA, USA",
+  "lat": 0,
+  "lon": 0
+}
+
+**Important:** Provide EITHER a location name OR latitude/longitude coordinates, never both. If using location name, set lat/lon to 0. Location should be specific (city, state/region, country) for best results.`,
+  schema: WeatherWidgetSchema,
+  execute: async (params, _) => {
+    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': 'Perplexica',
+            '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=${location.lon}&current=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
+          {
+            headers: {
+              'User-Agent': 'Perplexica',
+              'Content-Type': 'application/json',
+            },
+          },
+        );
+
+        const weatherData = await weatherRes.json();
+
+        return {
+          type: 'weather',
+          data: {
+            location: params.location,
+            latitude: location.lat,
+            longitude: location.lon,
+            current: weatherData.current,
+            hourly: {
+              time: weatherData.hourly.time.slice(0, 24),
+              temperature_2m: weatherData.hourly.temperature_2m.slice(0, 24),
+              precipitation_probability:
+                weatherData.hourly.precipitation_probability.slice(0, 24),
+              precipitation: weatherData.hourly.precipitation.slice(0, 24),
+              weather_code: weatherData.hourly.weather_code.slice(0, 24),
+            },
+            daily: weatherData.daily,
+            timezone: weatherData.timezone,
+          },
+        };
+      } else if (params.lat !== undefined && params.lon !== undefined) {
+        const [weatherRes, locationRes] = await Promise.all([
+          fetch(
+            `https://api.open-meteo.com/v1/forecast?latitude=${params.lat}&longitude=${params.lon}&current=temperature_2m,relative_humidity_2m,apparent_temperature,is_day,precipitation,rain,showers,snowfall,weather_code,cloud_cover,pressure_msl,surface_pressure,wind_speed_10m,wind_direction_10m,wind_gusts_10m&hourly=temperature_2m,precipitation_probability,precipitation,weather_code&daily=weather_code,temperature_2m_max,temperature_2m_min,precipitation_sum,precipitation_probability_max&timezone=auto&forecast_days=7`,
+            {
+              headers: {
+                'User-Agent': 'Perplexica',
+                'Content-Type': 'application/json',
+              },
+            },
+          ),
+          fetch(
+            `https://nominatim.openstreetmap.org/reverse?lat=${params.lat}&lon=${params.lon}&format=json`,
+            {
+              headers: {
+                'User-Agent': 'Perplexica',
+                'Content-Type': 'application/json',
+              },
+            },
+          ),
+        ]);
+
+        const weatherData = await weatherRes.json();
+        const locationData = await locationRes.json();
+
+        return {
+          type: 'weather',
+          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',
+        data: null,
+      };
+    } catch (err) {
+      return {
+        type: 'weather',
+        data: {
+          error: `Error fetching weather data: ${err}`,
+        },
+      };
+    }
+  },
+};
+export default weatherWidget;

src/lib/agents/suggestions/index.ts

@@ -1,32 +1,39 @@
-import ListLineOutputParser from '@/lib/outputParsers/listLineOutputParser';
-import { ChatPromptTemplate, PromptTemplate } from '@langchain/core/prompts';
 import formatChatHistoryAsString from '@/lib/utils/formatHistory';
-import { BaseMessage, HumanMessage, SystemMessage } from '@langchain/core/messages';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { suggestionGeneratorPrompt } from '@/lib/prompts/suggestions';
+import { ChatTurnMessage } from '@/lib/types';
+import z from 'zod';
+import BaseLLM from '@/lib/models/base/llm';
+import { i } from 'mathjs';
 
 type SuggestionGeneratorInput = {
-  chatHistory: BaseMessage[];
+  chatHistory: ChatTurnMessage[];
 };
 
-const outputParser = new ListLineOutputParser({
-  key: 'suggestions',
+const schema = z.object({
+  suggestions: z
+    .array(z.string())
+    .describe('List of suggested questions or prompts'),
 });
 
 const generateSuggestions = async (
   input: SuggestionGeneratorInput,
-  llm: BaseChatModel,
+  llm: BaseLLM<any>,
 ) => {
-  const chatPrompt = await ChatPromptTemplate.fromMessages([
-    new SystemMessage(suggestionGeneratorPrompt),
-    new HumanMessage(`<conversation>${formatChatHistoryAsString(input.chatHistory)}</conversation>`)
-  ]).formatMessages({})
+  const res = await llm.generateObject<z.infer<typeof schema>>({
+    messages: [
+      {
+        role: 'system',
+        content: suggestionGeneratorPrompt,
+      },
+      {
+        role: 'user',
+        content: `<chat_history>\n${formatChatHistoryAsString(input.chatHistory)}\n</chat_history>`,
+      },
+    ],
+    schema,
+  });
 
-  const res = await llm.invoke(chatPrompt)
-
-  const suggestions = await outputParser.invoke(res)
-
-  return suggestions
+  return res.suggestions;
 };
 
 export default generateSuggestions;

src/lib/db/migrate.ts

@@ -18,12 +18,18 @@ db.exec(`
 `);
 
 function sanitizeSql(content: string) {
-  return content
-    .split(/\r?\n/)
-    .filter(
-      (l) => !l.trim().startsWith('-->') && !l.includes('statement-breakpoint'),
+  const statements = content
+    .split(/--> statement-breakpoint/g)
+    .map((stmt) =>
+      stmt
+        .split(/\r?\n/)
+        .filter((l) => !l.trim().startsWith('-->'))
+        .join('\n')
+        .trim(),
     )
-    .join('\n');
+    .filter((stmt) => stmt.length > 0);
+
+  return statements;
 }
 
 fs.readdirSync(migrationsFolder)
@@ -32,7 +38,7 @@ fs.readdirSync(migrationsFolder)
   .forEach((file) => {
     const filePath = path.join(migrationsFolder, file);
     let content = fs.readFileSync(filePath, 'utf-8');
-    content = sanitizeSql(content);
+    const statements = sanitizeSql(content);
 
     const migrationName = file.split('_')[0] || file;
 
@@ -108,7 +114,12 @@ fs.readdirSync(migrationsFolder)
         db.exec('DROP TABLE messages;');
         db.exec('ALTER TABLE messages_with_sources RENAME TO messages;');
       } else {
-        db.exec(content);
+        // Execute each statement separately
+        statements.forEach((stmt) => {
+          if (stmt.trim()) {
+            db.exec(stmt);
+          }
+        });
       }
 
       db.prepare('INSERT OR IGNORE INTO ran_migrations (name) VALUES (?)').run(

src/lib/db/schema.ts

@@ -1,26 +1,23 @@
 import { sql } from 'drizzle-orm';
 import { text, integer, sqliteTable } from 'drizzle-orm/sqlite-core';
-import { Document } from '@langchain/core/documents';
+import { Block } from '../types';
 
 export const messages = sqliteTable('messages', {
   id: integer('id').primaryKey(),
-  role: text('type', { enum: ['assistant', 'user', 'source'] }).notNull(),
-  chatId: text('chatId').notNull(),
-  createdAt: text('createdAt')
-    .notNull()
-    .default(sql`CURRENT_TIMESTAMP`),
   messageId: text('messageId').notNull(),
-
-  content: text('content'),
-
-  sources: text('sources', {
-    mode: 'json',
-  })
-    .$type<Document[]>()
+  chatId: text('chatId').notNull(),
+  backendId: text('backendId').notNull(),
+  query: text('query').notNull(),
+  createdAt: text('createdAt').notNull(),
+  responseBlocks: text('responseBlocks', { mode: 'json' })
+    .$type<Block[]>()
     .default(sql`'[]'`),
+  status: text({ enum: ['answering', 'completed', 'error'] }).default(
+    'answering',
+  ),
 });
 
-interface File {
+interface DBFile {
   name: string;
   fileId: string;
 }
@@ -31,6 +28,6 @@ export const chats = sqliteTable('chats', {
   createdAt: text('createdAt').notNull(),
   focusMode: text('focusMode').notNull(),
   files: text('files', { mode: 'json' })
-    .$type<File[]>()
+    .$type<DBFile[]>()
     .default(sql`'[]'`),
 });

src/lib/hooks/useChat.tsx

@@ -1,13 +1,7 @@
 'use client';
 
-import {
-  AssistantMessage,
-  ChatTurn,
-  Message,
-  SourceMessage,
-  SuggestionMessage,
-  UserMessage,
-} from '@/components/ChatWindow';
+import { Message } from '@/components/ChatWindow';
+import { Block } from '@/lib/types';
 import {
   createContext,
   useContext,
@@ -22,20 +16,20 @@ import { toast } from 'sonner';
 import { getSuggestions } from '../actions';
 import { MinimalProvider } from '../models/types';
 import { getAutoMediaSearch } from '../config/clientRegistry';
+import { applyPatch } from 'rfc6902';
+import { Widget } from '@/components/ChatWindow';
 
 export type Section = {
-  userMessage: UserMessage;
-  assistantMessage: AssistantMessage | undefined;
-  parsedAssistantMessage: string | undefined;
-  speechMessage: string | undefined;
-  sourceMessage: SourceMessage | undefined;
+  message: Message;
+  widgets: Widget[];
+  parsedTextBlocks: string[];
+  speechMessage: string;
   thinkingEnded: boolean;
   suggestions?: string[];
 };
 
 type ChatContext = {
   messages: Message[];
-  chatTurns: ChatTurn[];
   sections: Section[];
   chatHistory: [string, string][];
   files: File[];
@@ -51,6 +45,8 @@ type ChatContext = {
   hasError: boolean;
   chatModelProvider: ChatModelProvider;
   embeddingModelProvider: EmbeddingModelProvider;
+  researchEnded: boolean;
+  setResearchEnded: (ended: boolean) => void;
   setOptimizationMode: (mode: string) => void;
   setFocusMode: (mode: string) => void;
   setFiles: (files: File[]) => void;
@@ -204,18 +200,26 @@ const loadMessages = async (
 
   setMessages(messages);
 
-  const chatTurns = messages.filter(
-    (msg): msg is ChatTurn => msg.role === 'user' || msg.role === 'assistant',
-  );
+  const history: [string, string][] = [];
+  messages.forEach((msg) => {
+    history.push(['human', msg.query]);
 
-  const history = chatTurns.map((msg) => {
-    return [msg.role, msg.content];
-  }) as [string, string][];
+    const textBlocks = msg.responseBlocks
+      .filter(
+        (block): block is Block & { type: 'text' } => block.type === 'text',
+      )
+      .map((block) => block.data)
+      .join('\n');
+
+    if (textBlocks) {
+      history.push(['assistant', textBlocks]);
+    }
+  });
 
   console.debug(new Date(), 'app:messages_loaded');
 
-  if (chatTurns.length > 0) {
-    document.title = chatTurns[0].content;
+  if (messages.length > 0) {
+    document.title = messages[0].query;
   }
 
   const files = data.chat.files.map((file: any) => {
@@ -246,12 +250,12 @@ export const chatContext = createContext<ChatContext>({
   loading: false,
   messageAppeared: false,
   messages: [],
-  chatTurns: [],
   sections: [],
   notFound: false,
   optimizationMode: '',
   chatModelProvider: { key: '', providerId: '' },
   embeddingModelProvider: { key: '', providerId: '' },
+  researchEnded: false,
   rewrite: () => {},
   sendMessage: async () => {},
   setFileIds: () => {},
@@ -260,6 +264,7 @@ export const chatContext = createContext<ChatContext>({
   setOptimizationMode: () => {},
   setChatModelProvider: () => {},
   setEmbeddingModelProvider: () => {},
+  setResearchEnded: () => {},
 });
 
 export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
@@ -273,6 +278,8 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
   const [loading, setLoading] = useState(false);
   const [messageAppeared, setMessageAppeared] = useState(false);
 
+  const [researchEnded, setResearchEnded] = useState(false);
+
   const [chatHistory, setChatHistory] = useState<[string, string][]>([]);
   const [messages, setMessages] = useState<Message[]>([]);
 
@@ -305,66 +312,44 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
 
   const messagesRef = useRef<Message[]>([]);
 
-  const chatTurns = useMemo((): ChatTurn[] => {
-    return messages.filter(
-      (msg): msg is ChatTurn => msg.role === 'user' || msg.role === 'assistant',
-    );
-  }, [messages]);
-
   const sections = useMemo<Section[]>(() => {
-    const sections: Section[] = [];
+    return messages.map((msg) => {
+      const textBlocks: string[] = [];
+      let speechMessage = '';
+      let thinkingEnded = false;
+      let suggestions: string[] = [];
 
-    messages.forEach((msg, i) => {
-      if (msg.role === 'user') {
-        const nextUserMessageIndex = messages.findIndex(
-          (m, j) => j > i && m.role === 'user',
-        );
+      const sourceBlocks = msg.responseBlocks.filter(
+        (block): block is Block & { type: 'source' } => block.type === 'source',
+      );
+      const sources = sourceBlocks.flatMap((block) => block.data);
 
-        const aiMessage = messages.find(
-          (m, j) =>
-            j > i &&
-            m.role === 'assistant' &&
-            (nextUserMessageIndex === -1 || j < nextUserMessageIndex),
-        ) as AssistantMessage | undefined;
+      const widgetBlocks = msg.responseBlocks
+        .filter((b) => b.type === 'widget')
+        .map((b) => b.data) as Widget[];
 
-        const sourceMessage = messages.find(
-          (m, j) =>
-            j > i &&
-            m.role === 'source' &&
-            m.sources &&
-            (nextUserMessageIndex === -1 || j < nextUserMessageIndex),
-        ) as SourceMessage | undefined;
-
-        let thinkingEnded = false;
-        let processedMessage = aiMessage?.content ?? '';
-        let speechMessage = aiMessage?.content ?? '';
-        let suggestions: string[] = [];
-
-        if (aiMessage) {
+      msg.responseBlocks.forEach((block) => {
+        if (block.type === 'text') {
+          let processedText = block.data;
           const citationRegex = /\[([^\]]+)\]/g;
           const regex = /\[(\d+)\]/g;
 
-          if (processedMessage.includes('<think>')) {
-            const openThinkTag =
-              processedMessage.match(/<think>/g)?.length || 0;
+          if (processedText.includes('<think>')) {
+            const openThinkTag = processedText.match(/<think>/g)?.length || 0;
             const closeThinkTag =
-              processedMessage.match(/<\/think>/g)?.length || 0;
+              processedText.match(/<\/think>/g)?.length || 0;
 
             if (openThinkTag && !closeThinkTag) {
-              processedMessage += '</think> <a> </a>';
+              processedText += '</think> <a> </a>';
             }
           }
 
-          if (aiMessage.content.includes('</think>')) {
+          if (block.data.includes('</think>')) {
             thinkingEnded = true;
           }
 
-          if (
-            sourceMessage &&
-            sourceMessage.sources &&
-            sourceMessage.sources.length > 0
-          ) {
-            processedMessage = processedMessage.replace(
+          if (sources.length > 0) {
+            processedText = processedText.replace(
               citationRegex,
               (_, capturedContent: string) => {
                 const numbers = capturedContent
@@ -379,7 +364,7 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
                       return `[${numStr}]`;
                     }
 
-                    const source = sourceMessage.sources?.[number - 1];
+                    const source = sources[number - 1];
                     const url = source?.metadata?.url;
 
                     if (url) {
@@ -393,37 +378,27 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
                 return linksHtml;
               },
             );
-            speechMessage = aiMessage.content.replace(regex, '');
+            speechMessage += block.data.replace(regex, '');
           } else {
-            processedMessage = processedMessage.replace(regex, '');
-            speechMessage = aiMessage.content.replace(regex, '');
+            processedText = processedText.replace(regex, '');
+            speechMessage += block.data.replace(regex, '');
           }
 
-          const suggestionMessage = messages.find(
-            (m, j) =>
-              j > i &&
-              m.role === 'suggestion' &&
-              (nextUserMessageIndex === -1 || j < nextUserMessageIndex),
-          ) as SuggestionMessage | undefined;
-
-          if (suggestionMessage && suggestionMessage.suggestions.length > 0) {
-            suggestions = suggestionMessage.suggestions;
-          }
+          textBlocks.push(processedText);
+        } else if (block.type === 'suggestion') {
+          suggestions = block.data;
         }
+      });
 
-        sections.push({
-          userMessage: msg,
-          assistantMessage: aiMessage,
-          sourceMessage: sourceMessage,
-          parsedAssistantMessage: processedMessage,
-          speechMessage,
-          thinkingEnded,
-          suggestions: suggestions,
-        });
-      }
+      return {
+        message: msg,
+        parsedTextBlocks: textBlocks,
+        speechMessage,
+        thinkingEnded,
+        suggestions,
+        widgets: widgetBlocks,
+      };
     });
-
-    return sections;
   }, [messages]);
 
   useEffect(() => {
@@ -489,24 +464,17 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
 
   const rewrite = (messageId: string) => {
     const index = messages.findIndex((msg) => msg.messageId === messageId);
-    const chatTurnsIndex = chatTurns.findIndex(
-      (msg) => msg.messageId === messageId,
-    );
 
     if (index === -1) return;
 
-    const message = chatTurns[chatTurnsIndex - 1];
+    setMessages((prev) => prev.slice(0, index));
 
-    setMessages((prev) => {
-      return [
-        ...prev.slice(0, messages.length > 2 ? messages.indexOf(message) : 0),
-      ];
-    });
     setChatHistory((prev) => {
-      return [...prev.slice(0, chatTurns.length > 2 ? chatTurnsIndex - 1 : 0)];
+      return prev.slice(0, index * 2);
     });
 
-    sendMessage(message.content, message.messageId, true);
+    const messageToRewrite = messages[index];
+    sendMessage(messageToRewrite.query, messageToRewrite.messageId, true);
   };
 
   useEffect(() => {
@@ -527,88 +495,165 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
   ) => {
     if (loading || !message) return;
     setLoading(true);
+    setResearchEnded(false);
     setMessageAppeared(false);
 
     if (messages.length <= 1) {
       window.history.replaceState(null, '', `/c/${chatId}`);
     }
 
-    let recievedMessage = '';
-    let added = false;
-
     messageId = messageId ?? crypto.randomBytes(7).toString('hex');
+    const backendId = crypto.randomBytes(20).toString('hex');
 
-    setMessages((prevMessages) => [
-      ...prevMessages,
-      {
-        content: message,
-        messageId: messageId,
-        chatId: chatId!,
-        role: 'user',
-        createdAt: new Date(),
-      },
-    ]);
+    const newMessage: Message = {
+      messageId,
+      chatId: chatId!,
+      backendId,
+      query: message,
+      responseBlocks: [],
+      status: 'answering',
+      createdAt: new Date(),
+    };
+
+    setMessages((prevMessages) => [...prevMessages, newMessage]);
+
+    const receivedTextRef = { current: '' };
 
     const messageHandler = async (data: any) => {
       if (data.type === 'error') {
         toast.error(data.data);
         setLoading(false);
+        setMessages((prev) =>
+          prev.map((msg) =>
+            msg.messageId === messageId
+              ? { ...msg, status: 'error' as const }
+              : msg,
+          ),
+        );
         return;
       }
 
+      if (data.type === 'researchComplete') {
+        setResearchEnded(true);
+        if (
+          newMessage.responseBlocks.find(
+            (b) => b.type === 'source' && b.data.length > 0,
+          )
+        ) {
+          setMessageAppeared(true);
+        }
+      }
+
+      if (data.type === 'block') {
+        setMessages((prev) =>
+          prev.map((msg) => {
+            if (msg.messageId === messageId) {
+              return {
+                ...msg,
+                responseBlocks: [...msg.responseBlocks, data.block],
+              };
+            }
+            return msg;
+          }),
+        );
+      }
+
+      if (data.type === 'updateBlock') {
+        setMessages((prev) =>
+          prev.map((msg) => {
+            if (msg.messageId === messageId) {
+              const updatedBlocks = msg.responseBlocks.map((block) => {
+                if (block.id === data.blockId) {
+                  const updatedBlock = { ...block };
+                  applyPatch(updatedBlock, data.patch);
+                  return updatedBlock;
+                }
+                return block;
+              });
+              return { ...msg, responseBlocks: updatedBlocks };
+            }
+            return msg;
+          }),
+        );
+      }
+
       if (data.type === 'sources') {
-        setMessages((prevMessages) => [
-          ...prevMessages,
-          {
-            messageId: data.messageId,
-            chatId: chatId!,
-            role: 'source',
-            sources: data.data,
-            createdAt: new Date(),
-          },
-        ]);
+        const sourceBlock: Block = {
+          id: crypto.randomBytes(7).toString('hex'),
+          type: 'source',
+          data: data.data,
+        };
+
+        setMessages((prev) =>
+          prev.map((msg) => {
+            if (msg.messageId === messageId) {
+              return {
+                ...msg,
+                responseBlocks: [...msg.responseBlocks, sourceBlock],
+              };
+            }
+            return msg;
+          }),
+        );
         if (data.data.length > 0) {
           setMessageAppeared(true);
         }
       }
 
       if (data.type === 'message') {
-        if (!added) {
-          setMessages((prevMessages) => [
-            ...prevMessages,
-            {
-              content: data.data,
-              messageId: data.messageId,
-              chatId: chatId!,
-              role: 'assistant',
-              createdAt: new Date(),
-            },
-          ]);
-          added = true;
-          setMessageAppeared(true);
-        } else {
-          setMessages((prev) =>
-            prev.map((message) => {
-              if (
-                message.messageId === data.messageId &&
-                message.role === 'assistant'
-              ) {
-                return { ...message, content: message.content + data.data };
-              }
+        receivedTextRef.current += data.data;
 
-              return message;
-            }),
-          );
-        }
-        recievedMessage += data.data;
+        setMessages((prev) =>
+          prev.map((msg) => {
+            if (msg.messageId === messageId) {
+              const existingTextBlockIndex = msg.responseBlocks.findIndex(
+                (b) => b.type === 'text',
+              );
+
+              if (existingTextBlockIndex >= 0) {
+                const updatedBlocks = [...msg.responseBlocks];
+                const existingBlock = updatedBlocks[
+                  existingTextBlockIndex
+                ] as Block & { type: 'text' };
+                updatedBlocks[existingTextBlockIndex] = {
+                  ...existingBlock,
+                  data: existingBlock.data + data.data,
+                };
+                return { ...msg, responseBlocks: updatedBlocks };
+              } else {
+                const textBlock: Block = {
+                  id: crypto.randomBytes(7).toString('hex'),
+                  type: 'text',
+                  data: data.data,
+                };
+                return {
+                  ...msg,
+                  responseBlocks: [...msg.responseBlocks, textBlock],
+                };
+              }
+            }
+            return msg;
+          }),
+        );
+        setMessageAppeared(true);
       }
 
       if (data.type === 'messageEnd') {
-        setChatHistory((prevHistory) => [
-          ...prevHistory,
+        const newHistory: [string, string][] = [
+          ...chatHistory,
           ['human', message],
-          ['assistant', recievedMessage],
-        ]);
+          ['assistant', receivedTextRef.current],
+        ];
+
+        setChatHistory(newHistory);
+
+        setMessages((prev) =>
+          prev.map((msg) =>
+            msg.messageId === messageId
+              ? { ...msg, status: 'completed' as const }
+              : msg,
+          ),
+        );
 
         setLoading(false);
 
@@ -626,38 +671,37 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
             ?.click();
         }
 
-        /* Check if there are sources after message id's index and no suggestions */
-
-        const userMessageIndex = messagesRef.current.findIndex(
-          (msg) => msg.messageId === messageId && msg.role === 'user',
+        // Check if there are sources and no suggestions
+        const currentMsg = messagesRef.current.find(
+          (msg) => msg.messageId === messageId,
         );
 
-        const sourceMessage = messagesRef.current.find(
-          (msg, i) => i > userMessageIndex && msg.role === 'source',
-        ) as SourceMessage | undefined;
-
-        const suggestionMessageIndex = messagesRef.current.findIndex(
-          (msg, i) => i > userMessageIndex && msg.role === 'suggestion',
+        const hasSourceBlocks = currentMsg?.responseBlocks.some(
+          (block) => block.type === 'source' && block.data.length > 0,
+        );
+        const hasSuggestions = currentMsg?.responseBlocks.some(
+          (block) => block.type === 'suggestion',
         );
 
-        if (
-          sourceMessage &&
-          sourceMessage.sources.length > 0 &&
-          suggestionMessageIndex == -1
-        ) {
-          const suggestions = await getSuggestions(messagesRef.current);
-          setMessages((prev) => {
-            return [
-              ...prev,
-              {
-                role: 'suggestion',
-                suggestions: suggestions,
-                chatId: chatId!,
-                createdAt: new Date(),
-                messageId: crypto.randomBytes(7).toString('hex'),
-              },
-            ];
-          });
+        if (hasSourceBlocks && !hasSuggestions) {
+          const suggestions = await getSuggestions(newHistory);
+          const suggestionBlock: Block = {
+            id: crypto.randomBytes(7).toString('hex'),
+            type: 'suggestion',
+            data: suggestions,
+          };
+
+          setMessages((prev) =>
+            prev.map((msg) => {
+              if (msg.messageId === messageId) {
+                return {
+                  ...msg,
+                  responseBlocks: [...msg.responseBlocks, suggestionBlock],
+                };
+              }
+              return msg;
+            }),
+          );
         }
       }
     };
@@ -726,7 +770,6 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
     <chatContext.Provider
       value={{
         messages,
-        chatTurns,
         sections,
         chatHistory,
         files,
@@ -750,6 +793,8 @@ export const ChatProvider = ({ children }: { children: React.ReactNode }) => {
         chatModelProvider,
         embeddingModelProvider,
         setEmbeddingModelProvider,
+        researchEnded,
+        setResearchEnded,
       }}
     >
       {children}

src/lib/models/base/embedding.ts

@@ -1,3 +1,5 @@
+import { Chunk } from '@/lib/types';
+
 abstract class BaseEmbedding<CONFIG> {
   constructor(protected config: CONFIG) {}
   abstract embedText(texts: string[]): Promise<number[][]>;

src/lib/models/base/llm.ts

@@ -1,10 +1,8 @@
 import {
   GenerateObjectInput,
-  GenerateObjectOutput,
   GenerateOptions,
   GenerateTextInput,
   GenerateTextOutput,
-  StreamObjectOutput,
   StreamTextOutput,
 } from '../types';
 
@@ -15,12 +13,10 @@ abstract class BaseLLM<CONFIG> {
   abstract streamText(
     input: GenerateTextInput,
   ): AsyncGenerator<StreamTextOutput>;
-  abstract generateObject<T>(
-    input: GenerateObjectInput,
-  ): Promise<GenerateObjectOutput<T>>;
+  abstract generateObject<T>(input: GenerateObjectInput): Promise<T>;
   abstract streamObject<T>(
     input: GenerateObjectInput,
-  ): AsyncGenerator<StreamObjectOutput<T>>;
+  ): AsyncGenerator<Partial<T>>;
 }
 
 export default BaseLLM;

src/lib/models/base/provider.ts

@@ -1,5 +1,3 @@
-import { Embeddings } from '@langchain/core/embeddings';
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { ModelList, ProviderMetadata } from '../types';
 import { UIConfigField } from '@/lib/config/types';
 import BaseLLM from './llm';

src/lib/models/providers/aiml.ts

@@ -1,152 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface AimlConfig {
-  apiKey: string;
-}
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'password',
-    name: 'API Key',
-    key: 'apiKey',
-    description: 'Your AI/ML API key',
-    required: true,
-    placeholder: 'AI/ML API Key',
-    env: 'AIML_API_KEY',
-    scope: 'server',
-  },
-];
-
-class AimlProvider extends BaseModelProvider<AimlConfig> {
-  constructor(id: string, name: string, config: AimlConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    try {
-      const res = await fetch('https://api.aimlapi.com/models', {
-        method: 'GET',
-        headers: {
-          'Content-Type': 'application/json',
-          Authorization: `Bearer ${this.config.apiKey}`,
-        },
-      });
-
-      const data = await res.json();
-
-      const chatModels: Model[] = data.data
-        .filter((m: any) => m.type === 'chat-completion')
-        .map((m: any) => {
-          return {
-            name: m.id,
-            key: m.id,
-          };
-        });
-
-      const embeddingModels: Model[] = data.data
-        .filter((m: any) => m.type === 'embedding')
-        .map((m: any) => {
-          return {
-            name: m.id,
-            key: m.id,
-          };
-        });
-
-      return {
-        embedding: embeddingModels,
-        chat: chatModels,
-      };
-    } catch (err) {
-      if (err instanceof TypeError) {
-        throw new Error(
-          'Error connecting to AI/ML API. Please ensure your API key is correct and the service is available.',
-        );
-      }
-
-      throw err;
-    }
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [
-        ...defaultModels.embedding,
-        ...configProvider.embeddingModels,
-      ],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading AI/ML API Chat Model. Invalid Model Selected',
-      );
-    }
-
-    return new ChatOpenAI({
-      apiKey: this.config.apiKey,
-      temperature: 0.7,
-      model: key,
-      configuration: {
-        baseURL: 'https://api.aimlapi.com',
-      },
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    const modelList = await this.getModelList();
-    const exists = modelList.embedding.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading AI/ML API Embedding Model. Invalid Model Selected.',
-      );
-    }
-
-    return new OpenAIEmbeddings({
-      apiKey: this.config.apiKey,
-      model: key,
-      configuration: {
-        baseURL: 'https://api.aimlapi.com',
-      },
-    });
-  }
-
-  static parseAndValidate(raw: any): AimlConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.apiKey)
-      throw new Error('Invalid config provided. API key must be provided');
-
-    return {
-      apiKey: String(raw.apiKey),
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'aiml',
-      name: 'AI/ML API',
-    };
-  }
-}
-
-export default AimlProvider;

src/lib/models/providers/anthropic.ts

@@ -1,115 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { ChatAnthropic } from '@langchain/anthropic';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface AnthropicConfig {
-  apiKey: string;
-}
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'password',
-    name: 'API Key',
-    key: 'apiKey',
-    description: 'Your Anthropic API key',
-    required: true,
-    placeholder: 'Anthropic API Key',
-    env: 'ANTHROPIC_API_KEY',
-    scope: 'server',
-  },
-];
-
-class AnthropicProvider extends BaseModelProvider<AnthropicConfig> {
-  constructor(id: string, name: string, config: AnthropicConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    const res = await fetch('https://api.anthropic.com/v1/models?limit=999', {
-      method: 'GET',
-      headers: {
-        'x-api-key': this.config.apiKey,
-        'anthropic-version': '2023-06-01',
-        'Content-type': 'application/json',
-      },
-    });
-
-    if (!res.ok) {
-      throw new Error(`Failed to fetch Anthropic models: ${res.statusText}`);
-    }
-
-    const data = (await res.json()).data;
-
-    const models: Model[] = data.map((m: any) => {
-      return {
-        key: m.id,
-        name: m.display_name,
-      };
-    });
-
-    return {
-      embedding: [],
-      chat: models,
-    };
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading Anthropic Chat Model. Invalid Model Selected',
-      );
-    }
-
-    return new ChatAnthropic({
-      apiKey: this.config.apiKey,
-      temperature: 0.7,
-      model: key,
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    throw new Error('Anthropic provider does not support embedding models.');
-  }
-
-  static parseAndValidate(raw: any): AnthropicConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.apiKey)
-      throw new Error('Invalid config provided. API key must be provided');
-
-    return {
-      apiKey: String(raw.apiKey),
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'anthropic',
-      name: 'Anthropic',
-    };
-  }
-}
-
-export default AnthropicProvider;

src/lib/models/providers/deepseek.ts

@@ -1,107 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { ChatOpenAI } from '@langchain/openai';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface DeepSeekConfig {
-  apiKey: string;
-}
-
-const defaultChatModels: Model[] = [
-  {
-    name: 'Deepseek Chat / DeepSeek V3.2 Exp',
-    key: 'deepseek-chat',
-  },
-  {
-    name: 'Deepseek Reasoner / DeepSeek V3.2 Exp',
-    key: 'deepseek-reasoner',
-  },
-];
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'password',
-    name: 'API Key',
-    key: 'apiKey',
-    description: 'Your DeepSeek API key',
-    required: true,
-    placeholder: 'DeepSeek API Key',
-    env: 'DEEPSEEK_API_KEY',
-    scope: 'server',
-  },
-];
-
-class DeepSeekProvider extends BaseModelProvider<DeepSeekConfig> {
-  constructor(id: string, name: string, config: DeepSeekConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    return {
-      embedding: [],
-      chat: defaultChatModels,
-    };
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading DeepSeek Chat Model. Invalid Model Selected',
-      );
-    }
-
-    return new ChatOpenAI({
-      apiKey: this.config.apiKey,
-      temperature: 0.7,
-      model: key,
-      configuration: {
-        baseURL: 'https://api.deepseek.com',
-      },
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    throw new Error('DeepSeek provider does not support embedding models.');
-  }
-
-  static parseAndValidate(raw: any): DeepSeekConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.apiKey)
-      throw new Error('Invalid config provided. API key must be provided');
-
-    return {
-      apiKey: String(raw.apiKey),
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'deepseek',
-      name: 'Deepseek AI',
-    };
-  }
-}
-
-export default DeepSeekProvider;

src/lib/models/providers/gemini.ts

@@ -1,145 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import {
-  ChatGoogleGenerativeAI,
-  GoogleGenerativeAIEmbeddings,
-} from '@langchain/google-genai';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface GeminiConfig {
-  apiKey: string;
-}
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'password',
-    name: 'API Key',
-    key: 'apiKey',
-    description: 'Your Google Gemini API key',
-    required: true,
-    placeholder: 'Google Gemini API Key',
-    env: 'GEMINI_API_KEY',
-    scope: 'server',
-  },
-];
-
-class GeminiProvider extends BaseModelProvider<GeminiConfig> {
-  constructor(id: string, name: string, config: GeminiConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    const res = await fetch(
-      `https://generativelanguage.googleapis.com/v1beta/models?key=${this.config.apiKey}`,
-      {
-        method: 'GET',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      },
-    );
-
-    const data = await res.json();
-
-    let defaultEmbeddingModels: Model[] = [];
-    let defaultChatModels: Model[] = [];
-
-    data.models.forEach((m: any) => {
-      if (
-        m.supportedGenerationMethods.some(
-          (genMethod: string) =>
-            genMethod === 'embedText' || genMethod === 'embedContent',
-        )
-      ) {
-        defaultEmbeddingModels.push({
-          key: m.name,
-          name: m.displayName,
-        });
-      } else if (m.supportedGenerationMethods.includes('generateContent')) {
-        defaultChatModels.push({
-          key: m.name,
-          name: m.displayName,
-        });
-      }
-    });
-
-    return {
-      embedding: defaultEmbeddingModels,
-      chat: defaultChatModels,
-    };
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [
-        ...defaultModels.embedding,
-        ...configProvider.embeddingModels,
-      ],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading Gemini Chat Model. Invalid Model Selected',
-      );
-    }
-
-    return new ChatGoogleGenerativeAI({
-      apiKey: this.config.apiKey,
-      temperature: 0.7,
-      model: key,
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    const modelList = await this.getModelList();
-    const exists = modelList.embedding.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading Gemini Embedding Model. Invalid Model Selected.',
-      );
-    }
-
-    return new GoogleGenerativeAIEmbeddings({
-      apiKey: this.config.apiKey,
-      model: key,
-    });
-  }
-
-  static parseAndValidate(raw: any): GeminiConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.apiKey)
-      throw new Error('Invalid config provided. API key must be provided');
-
-    return {
-      apiKey: String(raw.apiKey),
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'gemini',
-      name: 'Google Gemini',
-    };
-  }
-}
-
-export default GeminiProvider;

src/lib/models/providers/groq.ts

@@ -1,118 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { ChatGroq } from '@langchain/groq';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface GroqConfig {
-  apiKey: string;
-}
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'password',
-    name: 'API Key',
-    key: 'apiKey',
-    description: 'Your Groq API key',
-    required: true,
-    placeholder: 'Groq API Key',
-    env: 'GROQ_API_KEY',
-    scope: 'server',
-  },
-];
-
-class GroqProvider extends BaseModelProvider<GroqConfig> {
-  constructor(id: string, name: string, config: GroqConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    try {
-      const res = await fetch('https://api.groq.com/openai/v1/models', {
-        method: 'GET',
-        headers: {
-          'Content-Type': 'application/json',
-          Authorization: `Bearer ${this.config.apiKey}`,
-        },
-      });
-
-      const data = await res.json();
-
-      const models: Model[] = data.data.map((m: any) => {
-        return {
-          name: m.id,
-          key: m.id,
-        };
-      });
-
-      return {
-        embedding: [],
-        chat: models,
-      };
-    } catch (err) {
-      if (err instanceof TypeError) {
-        throw new Error(
-          'Error connecting to Groq API. Please ensure your API key is correct and the Groq service is available.',
-        );
-      }
-
-      throw err;
-    }
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error('Error Loading Groq Chat Model. Invalid Model Selected');
-    }
-
-    return new ChatGroq({
-      apiKey: this.config.apiKey,
-      temperature: 0.7,
-      model: key,
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    throw new Error('Groq provider does not support embedding models.');
-  }
-
-  static parseAndValidate(raw: any): GroqConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.apiKey)
-      throw new Error('Invalid config provided. API key must be provided');
-
-    return {
-      apiKey: String(raw.apiKey),
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'groq',
-      name: 'Groq',
-    };
-  }
-}
-
-export default GroqProvider;

src/lib/models/providers/lemonade.ts

@@ -1,158 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface LemonadeConfig {
-  baseURL: string;
-  apiKey?: string;
-}
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'string',
-    name: 'Base URL',
-    key: 'baseURL',
-    description: 'The base URL for Lemonade API',
-    required: true,
-    placeholder: 'https://api.lemonade.ai/v1',
-    env: 'LEMONADE_BASE_URL',
-    scope: 'server',
-  },
-  {
-    type: 'password',
-    name: 'API Key',
-    key: 'apiKey',
-    description: 'Your Lemonade API key (optional)',
-    required: false,
-    placeholder: 'Lemonade API Key',
-    env: 'LEMONADE_API_KEY',
-    scope: 'server',
-  },
-];
-
-class LemonadeProvider extends BaseModelProvider<LemonadeConfig> {
-  constructor(id: string, name: string, config: LemonadeConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    try {
-      const headers: Record<string, string> = {
-        'Content-Type': 'application/json',
-      };
-
-      if (this.config.apiKey) {
-        headers['Authorization'] = `Bearer ${this.config.apiKey}`;
-      }
-
-      const res = await fetch(`${this.config.baseURL}/models`, {
-        method: 'GET',
-        headers,
-      });
-
-      const data = await res.json();
-
-      const models: Model[] = data.data.map((m: any) => {
-        return {
-          name: m.id,
-          key: m.id,
-        };
-      });
-
-      return {
-        embedding: models,
-        chat: models,
-      };
-    } catch (err) {
-      if (err instanceof TypeError) {
-        throw new Error(
-          'Error connecting to Lemonade API. Please ensure the base URL is correct and the service is available.',
-        );
-      }
-
-      throw err;
-    }
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [
-        ...defaultModels.embedding,
-        ...configProvider.embeddingModels,
-      ],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading Lemonade Chat Model. Invalid Model Selected',
-      );
-    }
-
-    return new ChatOpenAI({
-      apiKey: this.config.apiKey || 'not-needed',
-      temperature: 0.7,
-      model: key,
-      configuration: {
-        baseURL: this.config.baseURL,
-      },
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    const modelList = await this.getModelList();
-    const exists = modelList.embedding.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading Lemonade Embedding Model. Invalid Model Selected.',
-      );
-    }
-
-    return new OpenAIEmbeddings({
-      apiKey: this.config.apiKey || 'not-needed',
-      model: key,
-      configuration: {
-        baseURL: this.config.baseURL,
-      },
-    });
-  }
-
-  static parseAndValidate(raw: any): LemonadeConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.baseURL)
-      throw new Error('Invalid config provided. Base URL must be provided');
-
-    return {
-      baseURL: String(raw.baseURL),
-      apiKey: raw.apiKey ? String(raw.apiKey) : undefined,
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'lemonade',
-      name: 'Lemonade',
-    };
-  }
-}
-
-export default LemonadeProvider;

src/lib/models/providers/lmstudio.ts

@@ -1,148 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-
-interface LMStudioConfig {
-  baseURL: string;
-}
-
-const providerConfigFields: UIConfigField[] = [
-  {
-    type: 'string',
-    name: 'Base URL',
-    key: 'baseURL',
-    description: 'The base URL for LM Studio server',
-    required: true,
-    placeholder: 'http://localhost:1234',
-    env: 'LM_STUDIO_BASE_URL',
-    scope: 'server',
-  },
-];
-
-class LMStudioProvider extends BaseModelProvider<LMStudioConfig> {
-  constructor(id: string, name: string, config: LMStudioConfig) {
-    super(id, name, config);
-  }
-
-  private normalizeBaseURL(url: string): string {
-    const trimmed = url.trim().replace(/\/+$/, '');
-    return trimmed.endsWith('/v1') ? trimmed : `${trimmed}/v1`;
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    try {
-      const baseURL = this.normalizeBaseURL(this.config.baseURL);
-
-      const res = await fetch(`${baseURL}/models`, {
-        method: 'GET',
-        headers: {
-          'Content-Type': 'application/json',
-        },
-      });
-
-      const data = await res.json();
-
-      const models: Model[] = data.data.map((m: any) => {
-        return {
-          name: m.id,
-          key: m.id,
-        };
-      });
-
-      return {
-        embedding: models,
-        chat: models,
-      };
-    } catch (err) {
-      if (err instanceof TypeError) {
-        throw new Error(
-          'Error connecting to LM Studio. Please ensure the base URL is correct and the LM Studio server is running.',
-        );
-      }
-
-      throw err;
-    }
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [
-        ...defaultModels.embedding,
-        ...configProvider.embeddingModels,
-      ],
-      chat: [...defaultModels.chat, ...configProvider.chatModels],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    const modelList = await this.getModelList();
-
-    const exists = modelList.chat.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading LM Studio Chat Model. Invalid Model Selected',
-      );
-    }
-
-    return new ChatOpenAI({
-      apiKey: 'lm-studio',
-      temperature: 0.7,
-      model: key,
-      streaming: true,
-      configuration: {
-        baseURL: this.normalizeBaseURL(this.config.baseURL),
-      },
-    });
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    const modelList = await this.getModelList();
-    const exists = modelList.embedding.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading LM Studio Embedding Model. Invalid Model Selected.',
-      );
-    }
-
-    return new OpenAIEmbeddings({
-      apiKey: 'lm-studio',
-      model: key,
-      configuration: {
-        baseURL: this.normalizeBaseURL(this.config.baseURL),
-      },
-    });
-  }
-
-  static parseAndValidate(raw: any): LMStudioConfig {
-    if (!raw || typeof raw !== 'object')
-      throw new Error('Invalid config provided. Expected object');
-    if (!raw.baseURL)
-      throw new Error('Invalid config provided. Base URL must be provided');
-
-    return {
-      baseURL: String(raw.baseURL),
-    };
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'lmstudio',
-      name: 'LM Studio',
-    };
-  }
-}
-
-export default LMStudioProvider;

src/lib/models/providers/ollama/ollamaEmbedding.ts

@@ -1,5 +1,6 @@
 import { Ollama } from 'ollama';
 import BaseEmbedding from '../../base/embedding';
+import { Chunk } from '@/lib/types';
 
 type OllamaConfig = {
   model: string;

src/lib/models/providers/ollama/ollamaLLM.ts

@@ -45,6 +45,7 @@ class OllamaLLM extends BaseLLM<OllamaConfig> {
         top_p: this.config.options?.topP,
         temperature: this.config.options?.temperature,
         num_predict: this.config.options?.maxTokens,
+        num_ctx: 32000,
         frequency_penalty: this.config.options?.frequencyPenalty,
         presence_penalty: this.config.options?.presencePenalty,
         stop: this.config.options?.stopSequences,
@@ -71,6 +72,7 @@ class OllamaLLM extends BaseLLM<OllamaConfig> {
       options: {
         top_p: this.config.options?.topP,
         temperature: this.config.options?.temperature,
+        num_ctx: 32000,
         num_predict: this.config.options?.maxTokens,
         frequency_penalty: this.config.options?.frequencyPenalty,
         presence_penalty: this.config.options?.presencePenalty,
@@ -96,9 +98,10 @@ class OllamaLLM extends BaseLLM<OllamaConfig> {
       model: this.config.model,
       messages: input.messages,
       format: z.toJSONSchema(input.schema),
+      think: false,
       options: {
         top_p: this.config.options?.topP,
-        temperature: this.config.options?.temperature,
+        temperature: 0.7,
         num_predict: this.config.options?.maxTokens,
         frequency_penalty: this.config.options?.frequencyPenalty,
         presence_penalty: this.config.options?.presencePenalty,
@@ -123,9 +126,10 @@ class OllamaLLM extends BaseLLM<OllamaConfig> {
       messages: input.messages,
       format: z.toJSONSchema(input.schema),
       stream: true,
+      think: false,
       options: {
         top_p: this.config.options?.topP,
-        temperature: this.config.options?.temperature,
+        temperature: 0.7,
         num_predict: this.config.options?.maxTokens,
         frequency_penalty: this.config.options?.frequencyPenalty,
         presence_penalty: this.config.options?.presencePenalty,

src/lib/models/providers/openai/index.ts

@@ -1,5 +1,3 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Embeddings } from '@langchain/core/embeddings';
 import { UIConfigField } from '@/lib/config/types';
 import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
 import { Model, ModelList, ProviderMetadata } from '../../types';

src/lib/models/providers/openai/openaiEmbedding.ts

@@ -1,5 +1,6 @@
 import OpenAI from 'openai';
 import BaseEmbedding from '../../base/embedding';
+import { Chunk } from '@/lib/types';
 
 type OpenAIConfig = {
   apiKey: string;

src/lib/models/providers/transformers.ts

@@ -1,87 +0,0 @@
-import { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import { Model, ModelList, ProviderMetadata } from '../types';
-import BaseModelProvider from './baseProvider';
-import { Embeddings } from '@langchain/core/embeddings';
-import { UIConfigField } from '@/lib/config/types';
-import { getConfiguredModelProviderById } from '@/lib/config/serverRegistry';
-import { HuggingFaceTransformersEmbeddings } from '@langchain/community/embeddings/huggingface_transformers';
-interface TransformersConfig {}
-
-const defaultEmbeddingModels: Model[] = [
-  {
-    name: 'all-MiniLM-L6-v2',
-    key: 'Xenova/all-MiniLM-L6-v2',
-  },
-  {
-    name: 'mxbai-embed-large-v1',
-    key: 'mixedbread-ai/mxbai-embed-large-v1',
-  },
-  {
-    name: 'nomic-embed-text-v1',
-    key: 'Xenova/nomic-embed-text-v1',
-  },
-];
-
-const providerConfigFields: UIConfigField[] = [];
-
-class TransformersProvider extends BaseModelProvider<TransformersConfig> {
-  constructor(id: string, name: string, config: TransformersConfig) {
-    super(id, name, config);
-  }
-
-  async getDefaultModels(): Promise<ModelList> {
-    return {
-      embedding: [...defaultEmbeddingModels],
-      chat: [],
-    };
-  }
-
-  async getModelList(): Promise<ModelList> {
-    const defaultModels = await this.getDefaultModels();
-    const configProvider = getConfiguredModelProviderById(this.id)!;
-
-    return {
-      embedding: [
-        ...defaultModels.embedding,
-        ...configProvider.embeddingModels,
-      ],
-      chat: [],
-    };
-  }
-
-  async loadChatModel(key: string): Promise<BaseChatModel> {
-    throw new Error('Transformers Provider does not support chat models.');
-  }
-
-  async loadEmbeddingModel(key: string): Promise<Embeddings> {
-    const modelList = await this.getModelList();
-    const exists = modelList.embedding.find((m) => m.key === key);
-
-    if (!exists) {
-      throw new Error(
-        'Error Loading OpenAI Embedding Model. Invalid Model Selected.',
-      );
-    }
-
-    return new HuggingFaceTransformersEmbeddings({
-      model: key,
-    });
-  }
-
-  static parseAndValidate(raw: any): TransformersConfig {
-    return {};
-  }
-
-  static getProviderConfigFields(): UIConfigField[] {
-    return providerConfigFields;
-  }
-
-  static getProviderMetadata(): ProviderMetadata {
-    return {
-      key: 'transformers',
-      name: 'Transformers',
-    };
-  }
-}
-
-export default TransformersProvider;

src/lib/models/registry.ts

@@ -1,7 +1,5 @@
 import { ConfigModelProvider } from '../config/types';
-import BaseModelProvider, {
-  createProviderInstance,
-} from './providers/baseProvider';
+import BaseModelProvider, { createProviderInstance } from './base/provider';
 import { getConfiguredModelProviders } from '../config/serverRegistry';
 import { providers } from './providers';
 import { MinimalProvider, ModelList } from './types';

src/lib/models/types.ts

@@ -1,4 +1,5 @@
 import z from 'zod';
+import { ChatTurnMessage } from '../types';
 
 type Model = {
   name: string;
@@ -37,7 +38,7 @@ type GenerateOptions = {
 };
 
 type GenerateTextInput = {
-  messages: Message[];
+  messages: ChatTurnMessage[];
   options?: GenerateOptions;
 };
 
@@ -54,7 +55,7 @@ type StreamTextOutput = {
 
 type GenerateObjectInput = {
   schema: z.ZodTypeAny;
-  messages: Message[];
+  messages: ChatTurnMessage[];
   options?: GenerateOptions;
 };
 

src/lib/outputParsers/lineOutputParser.ts

@@ -1,48 +0,0 @@
-import { BaseOutputParser } from '@langchain/core/output_parsers';
-
-interface LineOutputParserArgs {
-  key?: string;
-}
-
-class LineOutputParser extends BaseOutputParser<string | undefined> {
-  private key = 'questions';
-
-  constructor(args?: LineOutputParserArgs) {
-    super();
-    this.key = args?.key ?? this.key;
-  }
-
-  static lc_name() {
-    return 'LineOutputParser';
-  }
-
-  lc_namespace = ['langchain', 'output_parsers', 'line_output_parser'];
-
-  async parse(text: string): Promise<string | undefined> {
-    text = text.trim() || '';
-
-    const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
-    const startKeyIndex = text.indexOf(`<${this.key}>`);
-    const endKeyIndex = text.indexOf(`</${this.key}>`);
-
-    if (startKeyIndex === -1 || endKeyIndex === -1) {
-      return undefined;
-    }
-
-    const questionsStartIndex =
-      startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
-    const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
-    const line = text
-      .slice(questionsStartIndex, questionsEndIndex)
-      .trim()
-      .replace(regex, '');
-
-    return line;
-  }
-
-  getFormatInstructions(): string {
-    throw new Error('Not implemented.');
-  }
-}
-
-export default LineOutputParser;

src/lib/outputParsers/listLineOutputParser.ts

@@ -1,50 +0,0 @@
-import { BaseOutputParser } from '@langchain/core/output_parsers';
-
-interface LineListOutputParserArgs {
-  key?: string;
-}
-
-class LineListOutputParser extends BaseOutputParser<string[]> {
-  private key = 'questions';
-
-  constructor(args?: LineListOutputParserArgs) {
-    super();
-    this.key = args?.key ?? this.key;
-  }
-
-  static lc_name() {
-    return 'LineListOutputParser';
-  }
-
-  lc_namespace = ['langchain', 'output_parsers', 'line_list_output_parser'];
-
-  async parse(text: string): Promise<string[]> {
-    text = text.trim() || '';
-
-    const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
-    const startKeyIndex = text.indexOf(`<${this.key}>`);
-    const endKeyIndex = text.indexOf(`</${this.key}>`);
-
-    if (startKeyIndex === -1 || endKeyIndex === -1) {
-      return [];
-    }
-
-    const questionsStartIndex =
-      startKeyIndex === -1 ? 0 : startKeyIndex + `<${this.key}>`.length;
-    const questionsEndIndex = endKeyIndex === -1 ? text.length : endKeyIndex;
-    const lines = text
-      .slice(questionsStartIndex, questionsEndIndex)
-      .trim()
-      .split('\n')
-      .filter((line) => line.trim() !== '')
-      .map((line) => line.replace(regex, ''));
-
-    return lines;
-  }
-
-  getFormatInstructions(): string {
-    throw new Error('Not implemented.');
-  }
-}
-
-export default LineListOutputParser;

src/lib/prompts/index.ts

@@ -1,13 +0,0 @@
-import {
-  webSearchResponsePrompt,
-  webSearchRetrieverFewShots,
-  webSearchRetrieverPrompt,
-} from './webSearch';
-import { writingAssistantPrompt } from './writingAssistant';
-
-export default {
-  webSearchResponsePrompt,
-  webSearchRetrieverPrompt,
-  webSearchRetrieverFewShots,
-  writingAssistantPrompt,
-};

src/lib/prompts/media/image.ts

@@ -1,26 +1,29 @@
-import { BaseMessageLike } from "@langchain/core/messages";
+import { ChatTurnMessage } from '@/lib/types';
 
 export const imageSearchPrompt = `
 You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search the web for images.
 You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
-Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
+Output only the rephrased query in query key JSON format. Do not include any explanation or additional text.
 `;
 
-export const imageSearchFewShots: BaseMessageLike[] = [
-    [
-        'user',
-        '<conversation>\n</conversation>\n<follow_up>\nWhat is a cat?\n</follow_up>',
-    ],
-    ['assistant', '<query>A cat</query>'],
+export const imageSearchFewShots: ChatTurnMessage[] = [
+  {
+    role: 'user',
+    content:
+      '<conversation>\n</conversation>\n<follow_up>\nWhat is a cat?\n</follow_up>',
+  },
+  { role: 'assistant', content: '{"query":"A cat"}' },
 
-    [
-        'user',
-        '<conversation>\n</conversation>\n<follow_up>\nWhat is a car? How does it work?\n</follow_up>',
-    ],
-    ['assistant', '<query>Car working</query>'],
-    [
-        'user',
-        '<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
-    ],
-    ['assistant', '<query>AC working</query>']
-]
+  {
+    role: 'user',
+    content:
+      '<conversation>\n</conversation>\n<follow_up>\nWhat is a car? How does it work?\n</follow_up>',
+  },
+  { role: 'assistant', content: '{"query":"Car working"}' },
+  {
+    role: 'user',
+    content:
+      '<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
+  },
+  { role: 'assistant', content: '{"query":"AC working"}' },
+];

src/lib/prompts/media/videos.ts

@@ -1,25 +1,28 @@
-import { BaseMessageLike } from "@langchain/core/messages";
+import { ChatTurnMessage } from '@/lib/types';
 
 export const videoSearchPrompt = `
 You will be given a conversation below and a follow up question. You need to rephrase the follow-up question so it is a standalone question that can be used by the LLM to search Youtube for videos.
 You need to make sure the rephrased question agrees with the conversation and is relevant to the conversation.
-Output only the rephrased query wrapped in an XML <query> element. Do not include any explanation or additional text.
+Output only the rephrased query in query key JSON format. Do not include any explanation or additional text.
 `;
 
-export const videoSearchFewShots: BaseMessageLike[] = [
-    [
-        'user',
-        '<conversation>\n</conversation>\n<follow_up>\nHow does a car work?\n</follow_up>',
-    ],
-    ['assistant', '<query>How does a car work?</query>'],
-    [
-        'user',
-        '<conversation>\n</conversation>\n<follow_up>\nWhat is the theory of relativity?\n</follow_up>',
-    ],
-    ['assistant', '<query>Theory of relativity</query>'],
-    [
-        'user',
-        '<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
-    ],
-    ['assistant', '<query>AC working</query>'],
-]
+export const videoSearchFewShots: ChatTurnMessage[] = [
+  {
+    role: 'user',
+    content:
+      '<conversation>\n</conversation>\n<follow_up>\nHow does a car work?\n</follow_up>',
+  },
+  { role: 'assistant', content: '{"query":"How does a car work?"}' },
+  {
+    role: 'user',
+    content:
+      '<conversation>\n</conversation>\n<follow_up>\nWhat is the theory of relativity?\n</follow_up>',
+  },
+  { role: 'assistant', content: '{"query":"Theory of relativity"}' },
+  {
+    role: 'user',
+    content:
+      '<conversation>\n</conversation>\n<follow_up>\nHow does an AC work?\n</follow_up>',
+  },
+  { role: 'assistant', content: '{"query":"AC working"}' },
+];

src/lib/prompts/search/classifier.ts

@@ -0,0 +1,202 @@
+export const getClassifierPrompt = (input: {
+  intentDesc: string;
+  widgetDesc: string;
+}) => {
+  return `
+<role>
+You are an expert query classifier for an AI-powered search engine. Your task is to analyze user queries and determine the optimal strategy to answer them—selecting the right search intent(s) and widgets that will render in the UI.
+</role>
+
+<task>
+Given a conversation history and follow-up question, you must:
+1. Determine if search should be skipped (skipSearch: boolean)
+2. Generate a standalone, self-contained version of the question (standaloneFollowUp: string)
+3. Identify the intent(s) that describe how to fulfill the query (intent: array)
+4. Select appropriate widgets that will enhance the UI response (widgets: array)
+</task>
+
+## Understanding Your Tools
+
+**Intents** define HOW to find or generate information:
+- Different search methods: web search, forum discussions, academic papers, personal documents
+- Generation methods: direct response for greetings, creative writing
+- Each intent represents a different approach to answering the query
+- Multiple intents can be combined for comprehensive answers
+
+**Widgets** are UI components that render structured, real-time data:
+- They display specific types of information (weather forecasts, calculations, stock prices, etc.)
+- They provide interactive, visual elements that enhance the text response
+- They fetch data independently and render directly in the interface
+- They can work alone (widget-only answers) or alongside search results
+
+**Key distinction:** Intents determine the search/generation strategy, while widgets provide visual data enhancements in the UI.
+
+## The Philosophy of skipSearch
+
+Search connects you to external knowledge sources. Skip it only when external knowledge isn't needed.
+
+**Skip search (TRUE) when:**
+- Widgets alone can fully answer the query with their structured data
+- Simple greetings or social pleasantries
+- Pure creative writing requiring absolutely zero facts
+
+**Use search (FALSE) when:**
+- User is asking a question (what, how, why, when, where, who)
+- Any facts, explanations, or information are requested
+- Technical help, code, or learning content is needed
+- Current events, news, or time-sensitive information required
+- Widgets provide partial data but context/explanation needed
+- Uncertain - always default to searching
+
+**Critical rule:** If the user is ASKING about something or requesting INFORMATION, they need search. Question words (what, how, why, explain, tell me) strongly indicate skipSearch should be FALSE.
+
+## How Intents Work
+
+Available intent options:
+${input.intentDesc}
+
+**Understanding intent descriptions:**
+- Each intent description explains what it does and when to use it
+- Read the descriptions carefully to understand their purpose
+- Match user needs to the appropriate intent(s)
+- Can select multiple intents for comprehensive coverage
+
+**Selection strategy:**
+1. Identify what the user is asking for
+2. Review intent descriptions to find matches
+3. Select all relevant intents (can combine multiple)
+4. If user explicitly mentions a source (Reddit, research papers), use that specific intent
+5. Default to general web search for broad questions
+
+## How Widgets Work
+
+Available widget options:
+${input.widgetDesc}
+
+**Understanding widget descriptions:**
+- Each widget description explains what data it provides and how to use it
+- Widgets render as UI components alongside the text response
+- They enhance answers with visual, structured information
+- Review descriptions to identify applicable widgets
+
+**Selection strategy:**
+1. Identify if query needs any structured/real-time data
+2. Check widget descriptions for matches
+3. Include ALL applicable widgets (each type only once)
+4. Widgets work independently - include them even when also searching
+
+**Important widget behaviors:**
+- If widget fully answers query → skipSearch: TRUE, include widget, use widget_response intent
+- If widget provides partial data → skipSearch: FALSE, include widget + appropriate search intent(s)
+- Widgets and search intents coexist - they serve different purposes
+
+## Making Queries Standalone
+
+Transform follow-up questions to be understandable without conversation history:
+
+**Replace vague references:**
+- "it", "that", "this" → specific subjects from context
+- "they", "those" → actual entities being discussed  
+- "the previous one" → the actual item from history
+
+**Add necessary context:**
+- Include the topic being discussed
+- Reference specific subjects mentioned earlier
+- Preserve original meaning and scope
+- Don't over-elaborate or change intent
+
+**Example transformations:**
+- Context: Discussing React framework
+- Follow-up: "How does it work?" → Standalone: "How does React work?"
+- Follow-up: "What about hooks?" → Standalone: "What about React hooks?"
+
+## Critical Decision Framework
+
+Follow this decision tree IN ORDER:
+
+### 1. Widget-Only Queries
+**When:** Query can be fully answered by widget data alone
+**Then:** skipSearch: TRUE, intent: ['widget_response'], include widget(s)
+**Pattern:** Weather requests, calculations, unit conversions, stock prices (when no additional info needed)
+
+### 2. Greeting/Simple Writing Tasks  
+**When:** Just greetings OR pure creative writing with zero factual requirements
+**Then:** skipSearch: TRUE, intent: ['writing_task']
+**Pattern:** "hello", "hi", "write a birthday message", "compose a poem"
+**NEVER for:** Questions, explanations, definitions, facts, code help
+
+### 3. Widget + Additional Information
+**When:** Widget provides data but user wants more context/explanation
+**Then:** skipSearch: FALSE, intent: ['appropriate_search', 'widget_response'], include widget(s)
+**Pattern:** "weather in NYC and things to do", "AAPL stock and recent news"
+
+### 4. Pure Search Queries
+**When:** No widgets apply, just information/facts needed
+**Then:** skipSearch: FALSE, select appropriate search intent(s)
+**Strategy:**
+- Default to general web search
+- Use discussion search when user mentions Reddit, forums, opinions
+- Use academic search when user mentions research, papers, studies
+- Use private search when user references uploaded files/URLs
+- Can combine multiple search intents
+
+### 5. Think Before Setting skipSearch to TRUE
+**Ask yourself:**
+- Is the user ASKING about something? → FALSE
+- Is the user requesting INFORMATION? → FALSE  
+- Is there ANY factual component? → FALSE
+- Am I uncertain? → FALSE (default to search)
+
+## Intent Selection Rules
+
+Available intents:
+${input.intentDesc}
+
+**Rules:**
+- Include at least one intent when applicable
+- For information requests: default to general web search unless user specifies otherwise
+- Use specialized search intents when explicitly requested (discussions, academic, private)
+- Can combine multiple intents: ['academic_search', 'web_search']
+- widget_response: when widgets fully satisfy the query
+- writing_task: ONLY for greetings and simple creative writing (never for questions)
+
+## Widget Selection Rules
+
+Available widgets:
+${input.widgetDesc}
+
+**Rules:**
+- Include ALL applicable widgets regardless of skipSearch value
+- Each widget type can only be included once per query
+- Widgets render in the UI to enhance responses with structured data
+- Follow widget descriptions for proper parameter formatting
+
+## Output Format
+
+Your classification must be valid JSON:
+\`\`\`json
+{
+    "skipSearch": <true|false>,
+    "standaloneFollowUp": "<self-contained, contextualized query>",
+    "intent": ["<intent1>", "<intent2>"],
+    "widgets": [
+        {
+            "type": "<widget_type>",
+            "<param1>": "<value1>",
+            "<param2>": "<value2>"
+        }
+    ]
+}
+\`\`\`
+
+## Final Reminders
+
+- **Intents** = HOW to answer (search strategy, generation type)
+- **Widgets** = WHAT to display in UI (structured visual data)
+- **skipSearch** = Can answer without external search? (widgets alone, greetings, pure creativity)
+- **Default to FALSE** = When uncertain, search - better to search unnecessarily than miss information
+- **Read descriptions** = Intent and widget descriptions contain all the information you need to select them properly
+
+Your goal is to understand user intent and route requests through the optimal combination of search methods (intents) and UI enhancements (widgets). Pay close attention to what the user is actually asking for, not just pattern matching keywords.
+`;
+};

src/lib/prompts/search/researcher.ts

@@ -0,0 +1,255 @@
+export const getResearcherPrompt = (
+  actionDesc: string,
+  mode: 'speed' | 'balanced' | 'quality',
+  i: number,
+  maxIteration: number,
+) => {
+  const today = new Date().toLocaleDateString('en-US', {
+    year: 'numeric',
+    month: 'long',
+    day: 'numeric',
+  });
+
+  return `
+You are an action orchestrator. Your job is to fulfill user requests by selecting and executing appropriate actions - whether that's searching for information, creating calendar events, sending emails, or any other available action.
+You will be shared with the conversation history between user and AI, along with the user's latest follow-up question and your previous actions' results (if any. Note that they're per conversation so if they contain any previous actions it was executed for the last follow up (the one you're currently handling)). Based on this, you must decide the best next action(s) to take to fulfill the user's request.
+
+Today's date: ${today}
+
+You are operating in "${mode}" mode. ${
+    mode === 'speed'
+      ? 'Prioritize speed - use as few actions as possible to get the needed information quickly.'
+      : mode === 'balanced'
+        ? 'Balance speed and depth - use a moderate number of actions to get good information efficiently. Never stop at the first action unless there is no action available or the query is simple.'
+        : 'Conduct deep research - use multiple actions to gather comprehensive information, even if it takes longer.'
+  }
+
+You are currently on iteration ${i + 1} of your research process and have ${maxIteration} total iterations so please take action accordingly. After max iterations, the done action would get called automatically so you don't have to worry about that unless you want to end the research early.
+
+<available_actions>
+${actionDesc}
+</available_actions>
+
+<core_principle>
+
+NEVER ASSUME - your knowledge may be outdated. When a user asks about something you're not certain about, go find out. Don't assume it exists or doesn't exist - just look it up directly.
+
+</core_principle>
+
+<reasoning_approach>
+
+Think like a human would. Your reasoning should be natural and show:
+- What the user is asking for
+- What you need to find out or do
+- Your plan to accomplish it
+
+Keep it to 2-3 natural sentences.
+
+</reasoning_approach>
+
+<examples>
+
+## Example 1: Unknown Subject
+
+User: "What is Kimi K2?"
+
+Good reasoning:
+"I'm not sure what Kimi K2 is - could be an AI model, a product, or something else. Let me look it up to find out what it actually is and get the relevant details."
+
+Actions: web_search ["Kimi K2", "Kimi K2 AI"]
+
+## Example 2: Subject You're Uncertain About
+
+User: "What are the features of GPT-5.1?"
+
+Good reasoning:
+"I don't have current information on GPT-5.1 - my knowledge might be outdated. Let me look up GPT-5.1 to see what's available and what features it has."
+
+Actions: web_search ["GPT-5.1", "GPT-5.1 features", "GPT-5.1 release"]
+
+Bad reasoning (wastes time on verification):
+"GPT-5.1 might not exist based on my knowledge. I need to verify if it exists first before looking for features."
+
+## Example 3: After Actions Return Results
+
+User: "What are the features of GPT-5.1?"
+[Previous actions returned information about GPT-5.1]
+
+Good reasoning:
+"Got the information I needed about GPT-5.1. The results cover its features and capabilities - I can now provide a complete answer."
+
+Action: done
+
+## Example 4: Ambiguous Query
+
+User: "Tell me about Mercury"
+
+Good reasoning:
+"Mercury could refer to several things - the planet, the element, or something else. I'll look up both main interpretations to give a useful answer."
+
+Actions: web_search ["Mercury planet facts", "Mercury element"]
+
+## Example 5: Current Events
+
+User: "What's happening with AI regulation?"
+
+Good reasoning:
+"I need current news on AI regulation developments. Let me find the latest updates on this topic."
+
+Actions: web_search ["AI regulation news 2024", "AI regulation bill latest"]
+
+## Example 6: Technical Query
+
+User: "How do I set up authentication in Next.js 14?"
+
+Good reasoning:
+"This is a technical implementation question. I'll find the current best practices and documentation for Next.js 14 authentication."
+
+Actions: web_search ["Next.js 14 authentication guide", "NextAuth.js App Router"]
+
+## Example 7: Comparison Query
+
+User: "Prisma vs Drizzle - which should I use?"
+
+Good reasoning:
+"Need to find factual comparisons between these ORMs - performance, features, trade-offs. Let me gather objective information."
+
+Actions: web_search ["Prisma vs Drizzle comparison 2024", "Drizzle ORM performance"]
+
+## Example 8: Fact-Check
+
+User: "Is it true you only use 10% of your brain?"
+
+Good reasoning:
+"This is a common claim that needs scientific verification. Let me find what the actual research says about this."
+
+Actions: web_search ["10 percent brain myth science", "brain usage neuroscience"]
+
+## Example 9: Recent Product
+
+User: "What are the specs of MacBook Pro M4?"
+
+Good reasoning:
+"I need current information on the MacBook Pro M4. Let me look up the latest specs and details."
+
+Actions: web_search ["MacBook Pro M4 specs", "MacBook Pro M4 specifications Apple"]
+
+## Example 10: Multi-Part Query
+
+User: "Population of Tokyo vs New York?"
+
+Good reasoning:
+"Need current population stats for both cities. I'll look up the comparison data."
+
+Actions: web_search ["Tokyo population 2024", "Tokyo vs New York population"]
+
+## Example 11: Calendar Task
+
+User: "Add a meeting with John tomorrow at 3pm"
+
+Good reasoning:
+"This is a calendar task. I have all the details - meeting with John, tomorrow, 3pm. I'll create the event."
+
+Action: create_calendar_event with the provided details
+
+## Example 12: Email Task
+
+User: "Send an email to sarah@company.com about the project update"
+
+Good reasoning:
+"Need to send an email. I have the recipient but need to compose appropriate content about the project update."
+
+Action: send_email to sarah@company.com with project update content
+
+## Example 13: Multi-Step Task
+
+User: "What's the weather in Tokyo and add a reminder to pack an umbrella if it's rainy"
+
+Good reasoning:
+"Two things here - first I need to check Tokyo's weather, then based on that I might need to create a reminder. Let me start with the weather lookup."
+
+Actions: web_search ["Tokyo weather today forecast"]
+
+## Example 14: Research Then Act
+
+User: "Find the best Italian restaurant near me and make a reservation for 7pm"
+
+Good reasoning:
+"I need to first find top Italian restaurants in the area, then make a reservation. Let me start by finding the options."
+
+Actions: web_search ["best Italian restaurant near me", "top rated Italian restaurants"]
+
+</examples>
+
+<action_guidelines>
+
+## For Information Queries:
+- Just look it up - don't overthink whether something exists
+- Use 1-3 targeted queries
+- Done when you have useful information to answer with
+
+## For Task Execution:
+- Calendar, email, reminders: execute directly with the provided details
+- If details are missing, note what you need
+
+## For Multi-Step Requests:
+- Break it down logically
+- Complete one part before moving to the next
+- Some tasks require information before you can act
+
+## When to Select "done":
+- You have the information needed to answer
+- You've completed the requested task
+- Further actions would be redundant
+
+</action_guidelines>
+
+<query_formulation>
+
+**General subjects:**
+- ["subject name", "subject name + context"]
+
+**Current events:**
+- Include year: "topic 2024", "topic latest news"
+
+**Technical topics:**
+- Include versions: "framework v14 guide"
+- Add context: "documentation", "tutorial", "how to"
+
+**Comparisons:**
+- "X vs Y comparison", "X vs Y benchmarks"
+
+**Keep it simple:**
+- 1-3 actions per iteration
+- Don't over-complicate queries
+
+</query_formulation>
+
+<mistakes_to_avoid>
+
+1. **Over-assuming**: Don't assume things exist or don't exist - just look them up
+
+2. **Verification obsession**: Don't waste actions "verifying existence" - just search for the thing directly
+
+3. **Endless loops**: If 2-3 actions don't find something, it probably doesn't exist - report that and move on
+
+4. **Ignoring task context**: If user wants a calendar event, don't just search - create the event
+
+5. **Overthinking**: Keep reasoning simple and action-focused
+
+</mistakes_to_avoid>
+
+<output_format>
+Reasoning should be 2-3 natural sentences showing your thought process and plan. Then select and configure the appropriate action(s).
+
+Always respond in the following JSON format and never deviate from it or output any extra text:
+{
+  "reasoning": "<your reasoning here>",
+  "actions": [
+    {"type": "<action_type>", "param1": "value1", "...": "..."},
+    ...
+  ]
+}
+</output_format>
+`;
+};

src/lib/prompts/search/writer.ts

@@ -1,94 +1,5 @@
-import { BaseMessageLike } from '@langchain/core/messages';
-
-export const webSearchRetrieverPrompt = `
-You are an AI question rephraser. You will be given a conversation and a follow-up question,  you will have to rephrase the follow up question so it is a standalone question and can be used by another LLM to search the web for information to answer it.
-If it is a simple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
-If the user asks some question from some URL or wants you to summarize a PDF or a webpage (via URL) you need to return the links inside the \`links\` XML block and the question inside the \`question\` XML block. If the user wants to you to summarize the webpage or the PDF you need to return \`summarize\` inside the \`question\` XML block in place of a question and the link to summarize in the \`links\` XML block.
-You must always return the rephrased question inside the \`question\` XML block, if there are no links in the follow-up question then don't insert a \`links\` XML block in your response.
-
-**Note**: All user messages are individual entities and should be treated as such do not mix conversations.
-`;
-
-export const webSearchRetrieverFewShots: BaseMessageLike[] = [
-  [
-    'user',
-    `<conversation>
-</conversation>
-<query>
-What is the capital of France
-</query>`,
-  ],
-  [
-    'assistant',
-    `<question>
-Capital of france
-</question>`,
-  ],
-  [
-    'user',
-    `<conversation>
-</conversation>
-<query>
-Hi, how are you?
-</query>`,
-  ],
-  [
-    'assistant',
-    `<question>
-not_needed
-</question>`,
-  ],
-  [
-    'user',
-    `<conversation>
-</conversation>
-<query>
-What is Docker?
-</query>`,
-  ],
-  [
-    'assistant',
-    `<question>
-What is Docker
-</question>`,
-  ],
-  [
-    'user',
-    `<conversation>
-</conversation>
-<query>
-Can you tell me what is X from https://example.com
-</query>`,
-  ],
-  [
-    'assistant',
-    `<question>
-What is X?
-</question>
-<links>
-https://example.com
-</links>`,
-  ],
-  [
-    'user',
-    `<conversation>
-</conversation>
-<query>
-Summarize the content from https://example.com
-</query>`,
-  ],
-  [
-    'assistant',
-    `<question>
-summarize
-</question>
-<links>
-https://example.com
-</links>`,
-  ],
-];
-
-export const webSearchResponsePrompt = `
+export const getWriterPrompt = (context: string) => {
+  return `
     You are Perplexica, an AI model skilled in web search and crafting detailed, engaging, and well-structured answers. You excel at summarizing web pages and extracting relevant information to create professional, blog-style responses.
 
     Your task is to provide answers that are:
@@ -105,6 +16,8 @@ export const webSearchResponsePrompt = `
     - **Length and Depth**: Provide comprehensive coverage of the topic. Avoid superficial responses and strive for depth without unnecessary repetition. Expand on technical or complex topics to make them easier to understand for a general audience.
     - **No main heading/title**: Start your response directly with the introduction unless asked to provide a specific title.
     - **Conclusion or Summary**: Include a concluding paragraph that synthesizes the provided information or suggests potential next steps, where appropriate.
+    - **No references or source list at the end**: Do not include a seperate references or sources section at the end of your response. All references are sent to user by the system automatically.
+    - **Do not give the mapping of citations to sources**: Only use the [number] notation in the text. Never return the mapping of citations to sources.
 
     ### Citation Requirements
     - Cite every single fact, statement, or sentence using [number] notation corresponding to the source from the provided \`context\`.
@@ -113,25 +26,33 @@ export const webSearchResponsePrompt = `
     - Use multiple sources for a single detail if applicable, such as, "Paris is a cultural hub, attracting millions of visitors annually[1][2]."
     - Always prioritize credibility and accuracy by linking all statements back to their respective context sources.
     - Avoid citing unsupported assumptions or personal interpretations; if no source supports a statement, clearly indicate the limitation.
+    - Avoid citing widget data but you can use it to directly answer without citation.
+    - Never return the mapping of citations to sources; only use the [number] notation in the text. Never return a references or sources section seperately.
+
+    ### Widget Data Usage
+    - Widget data provided in the context can be used directly to answer specific queries (e.g., current weather, stock prices, calculations) without citations.
+    - The widget data is already displayed to the user in a beautiful format (via cards, tables, etc) just before your response so you don't need to generate a very detailed response for widget data. Provide concise answers for such queries.
+    - You can also mention that for more information you can look at the widget displayed above.
+    - For weather data, only provide current weather conditions not forecasts unless explicitly asked for forecasts by the user.
+    - You don't need to cite widget data you can directly use it to answer the user query. NEVER CITE widget OR (any other notation) TO CITE WIDGET DATA.
 
     ### Special Instructions
     - If the query involves technical, historical, or complex topics, provide detailed background and explanatory sections to ensure clarity.
     - If the user provides vague input or if relevant information is missing, explain what additional details might help refine the search.
     - If no relevant information is found, say: "Hmm, sorry I could not find any relevant information on this topic. Would you like me to search again or ask something else?" Be transparent about limitations and suggest alternatives or ways to reframe the query.
-
-    ### User instructions
-    These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
-    {systemInstructions}
+    - If its a simple query (like weather, calculations, definitions), provide concise answers and not a long article.
 
     ### Example Output
     - Begin with a brief introduction summarizing the event or query topic.
     - Follow with detailed sections under clear headings, covering all aspects of the query if possible.
     - Provide explanations or historical context as needed to enhance understanding.
     - End with a conclusion or overall perspective if relevant.
+    - For simpler queries like weather, calculations, or definitions, provide concise answers and not a long article.
 
     <context>
-    {context}
+    ${context}
     </context>
 
-    Current date & time in ISO format (UTC timezone) is: {date}.
-`;
+    Current date & time in ISO format (UTC timezone) is: ${new Date().toISOString()}.
+    `;
+};

src/lib/prompts/suggestions/index.ts

@@ -3,13 +3,15 @@ You are an AI suggestion generator for an AI powered search engine. You will be
 You need to make sure the suggestions are relevant to the conversation and are helpful to the user. Keep a note that the user might use these suggestions to ask a chat model for more information. 
 Make sure the suggestions are medium in length and are informative and relevant to the conversation.
 
-Provide these suggestions separated by newlines between the XML tags <suggestions> and </suggestions>. For example:
-
-<suggestions>
-Tell me more about SpaceX and their recent projects
-What is the latest news on SpaceX?
-Who is the CEO of SpaceX?
-</suggestions>
+Sample suggestions for a conversation about Elon Musk:
+{
+    "suggestions": [
+        "What are Elon Musk's plans for SpaceX in the next decade?",
+        "How has Tesla's stock performance been influenced by Elon Musk's leadership?",
+        "What are the key innovations introduced by Elon Musk in the electric vehicle industry?",
+        "How does Elon Musk's vision for renewable energy impact global sustainability efforts?"
+    ]
+}
 
 Today's date is ${new Date().toISOString()}
 `;

src/lib/prompts/writingAssistant.ts

@@ -1,17 +0,0 @@
-export const writingAssistantPrompt = `
-You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query. 
-Since you are a writing assistant, you would not perform web searches. If you think you lack information to answer the query, you can ask the user for more information or suggest them to switch to a different focus mode.
-You will be shared a context that can contain information from files user has uploaded to get answers from. You will have to generate answers upon that.
-
-You have to cite the answer using [number] notation. You must cite the sentences with their relevent context number. You must cite each and every part of the answer so the user can know where the information is coming from.
-Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2].
-However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer.
-
-### User instructions
-These instructions are shared to you by the user and not by the system. You will have to follow them but give them less priority than the above instructions. If the user has provided specific instructions or preferences, incorporate them into your response while adhering to the overall guidelines.
-{systemInstructions}
-
-<context>
-{context}
-</context>
-`;

src/lib/search/index.ts

@@ -1,59 +0,0 @@
-import MetaSearchAgent from '@/lib/search/metaSearchAgent';
-import prompts from '../prompts';
-
-export const searchHandlers: Record<string, MetaSearchAgent> = {
-  webSearch: new MetaSearchAgent({
-    activeEngines: [],
-    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
-    responsePrompt: prompts.webSearchResponsePrompt,
-    queryGeneratorFewShots: prompts.webSearchRetrieverFewShots,
-    rerank: true,
-    rerankThreshold: 0.3,
-    searchWeb: true,
-  }),
-  academicSearch: new MetaSearchAgent({
-    activeEngines: ['arxiv', 'google scholar', 'pubmed'],
-    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
-    responsePrompt: prompts.webSearchResponsePrompt,
-    queryGeneratorFewShots: prompts.webSearchRetrieverFewShots,
-    rerank: true,
-    rerankThreshold: 0,
-    searchWeb: true,
-  }),
-  writingAssistant: new MetaSearchAgent({
-    activeEngines: [],
-    queryGeneratorPrompt: '',
-    queryGeneratorFewShots: [],
-    responsePrompt: prompts.writingAssistantPrompt,
-    rerank: true,
-    rerankThreshold: 0,
-    searchWeb: false,
-  }),
-  wolframAlphaSearch: new MetaSearchAgent({
-    activeEngines: ['wolframalpha'],
-    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
-    responsePrompt: prompts.webSearchResponsePrompt,
-    queryGeneratorFewShots: prompts.webSearchRetrieverFewShots,
-    rerank: false,
-    rerankThreshold: 0,
-    searchWeb: true,
-  }),
-  youtubeSearch: new MetaSearchAgent({
-    activeEngines: ['youtube'],
-    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
-    responsePrompt: prompts.webSearchResponsePrompt,
-    queryGeneratorFewShots: prompts.webSearchRetrieverFewShots,
-    rerank: true,
-    rerankThreshold: 0.3,
-    searchWeb: true,
-  }),
-  redditSearch: new MetaSearchAgent({
-    activeEngines: ['reddit'],
-    queryGeneratorPrompt: prompts.webSearchRetrieverPrompt,
-    responsePrompt: prompts.webSearchResponsePrompt,
-    queryGeneratorFewShots: prompts.webSearchRetrieverFewShots,
-    rerank: true,
-    rerankThreshold: 0.3,
-    searchWeb: true,
-  }),
-};

src/lib/search/metaSearchAgent.ts

@@ -1,514 +0,0 @@
-import { ChatOpenAI } from '@langchain/openai';
-import type { BaseChatModel } from '@langchain/core/language_models/chat_models';
-import type { Embeddings } from '@langchain/core/embeddings';
-import {
-  ChatPromptTemplate,
-  MessagesPlaceholder,
-  PromptTemplate,
-} from '@langchain/core/prompts';
-import {
-  RunnableLambda,
-  RunnableMap,
-  RunnableSequence,
-} from '@langchain/core/runnables';
-import { BaseMessage, BaseMessageLike } from '@langchain/core/messages';
-import { StringOutputParser } from '@langchain/core/output_parsers';
-import LineListOutputParser from '../outputParsers/listLineOutputParser';
-import LineOutputParser from '../outputParsers/lineOutputParser';
-import { getDocumentsFromLinks } from '../utils/documents';
-import { Document } from '@langchain/core/documents';
-import { searchSearxng } from '../searxng';
-import path from 'node:path';
-import fs from 'node:fs';
-import computeSimilarity from '../utils/computeSimilarity';
-import formatChatHistoryAsString from '../utils/formatHistory';
-import eventEmitter from 'events';
-import { StreamEvent } from '@langchain/core/tracers/log_stream';
-
-export interface MetaSearchAgentType {
-  searchAndAnswer: (
-    message: string,
-    history: BaseMessage[],
-    llm: BaseChatModel,
-    embeddings: Embeddings,
-    optimizationMode: 'speed' | 'balanced' | 'quality',
-    fileIds: string[],
-    systemInstructions: string,
-  ) => Promise<eventEmitter>;
-}
-
-interface Config {
-  searchWeb: boolean;
-  rerank: boolean;
-  rerankThreshold: number;
-  queryGeneratorPrompt: string;
-  queryGeneratorFewShots: BaseMessageLike[];
-  responsePrompt: string;
-  activeEngines: string[];
-}
-
-type BasicChainInput = {
-  chat_history: BaseMessage[];
-  query: string;
-};
-
-class MetaSearchAgent implements MetaSearchAgentType {
-  private config: Config;
-  private strParser = new StringOutputParser();
-
-  constructor(config: Config) {
-    this.config = config;
-  }
-
-  private async createSearchRetrieverChain(llm: BaseChatModel) {
-    (llm as unknown as ChatOpenAI).temperature = 0;
-
-    return RunnableSequence.from([
-      ChatPromptTemplate.fromMessages([
-        ['system', this.config.queryGeneratorPrompt],
-        ...this.config.queryGeneratorFewShots,
-        [
-          'user',
-          `
-        <conversation>
-        {chat_history}
-        </conversation>
-
-        <query>
-        {query}
-        </query>
-       `,
-        ],
-      ]),
-      llm,
-      this.strParser,
-      RunnableLambda.from(async (input: string) => {
-        const linksOutputParser = new LineListOutputParser({
-          key: 'links',
-        });
-
-        const questionOutputParser = new LineOutputParser({
-          key: 'question',
-        });
-
-        const links = await linksOutputParser.parse(input);
-        let question = (await questionOutputParser.parse(input)) ?? input;
-
-        if (question === 'not_needed') {
-          return { query: '', docs: [] };
-        }
-
-        if (links.length > 0) {
-          if (question.length === 0) {
-            question = 'summarize';
-          }
-
-          let docs: Document[] = [];
-
-          const linkDocs = await getDocumentsFromLinks({ links });
-
-          const docGroups: Document[] = [];
-
-          linkDocs.map((doc) => {
-            const URLDocExists = docGroups.find(
-              (d) =>
-                d.metadata.url === doc.metadata.url &&
-                d.metadata.totalDocs < 10,
-            );
-
-            if (!URLDocExists) {
-              docGroups.push({
-                ...doc,
-                metadata: {
-                  ...doc.metadata,
-                  totalDocs: 1,
-                },
-              });
-            }
-
-            const docIndex = docGroups.findIndex(
-              (d) =>
-                d.metadata.url === doc.metadata.url &&
-                d.metadata.totalDocs < 10,
-            );
-
-            if (docIndex !== -1) {
-              docGroups[docIndex].pageContent =
-                docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
-              docGroups[docIndex].metadata.totalDocs += 1;
-            }
-          });
-
-          await Promise.all(
-            docGroups.map(async (doc) => {
-              const res = await llm.invoke(`
-            You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the 
-            text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
-            If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
-            
-            - **Journalistic tone**: The summary should sound professional and journalistic, not too casual or vague.
-            - **Thorough and detailed**: Ensure that every key point from the text is captured and that the summary directly answers the query.
-            - **Not too lengthy, but detailed**: The summary should be informative but not excessively long. Focus on providing detailed information in a concise format.
-
-            The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
-
-            <example>
-            1. \`<text>
-            Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers. 
-            It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications 
-            by using containers.
-            </text>
-
-            <query>
-            What is Docker and how does it work?
-            </query>
-
-            Response:
-            Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application 
-            deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in 
-            any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
-            \`
-            2. \`<text>
-            The theory of relativity, or simply relativity, encompasses two interrelated theories of Albert Einstein: special relativity and general
-            relativity. However, the word "relativity" is sometimes used in reference to Galilean invariance. The term "theory of relativity" was based
-            on the expression "relative theory" used by Max Planck in 1906. The theory of relativity usually encompasses two interrelated theories by
-            Albert Einstein: special relativity and general relativity. Special relativity applies to all physical phenomena in the absence of gravity.
-            General relativity explains the law of gravitation and its relation to other forces of nature. It applies to the cosmological and astrophysical
-            realm, including astronomy.
-            </text>
-
-            <query>
-            summarize
-            </query>
-
-            Response:
-            The theory of relativity, developed by Albert Einstein, encompasses two main theories: special relativity and general relativity. Special
-            relativity applies to all physical phenomena in the absence of gravity, while general relativity explains the law of gravitation and its
-            relation to other forces of nature. The theory of relativity is based on the concept of "relative theory," as introduced by Max Planck in
-            1906. It is a fundamental theory in physics that has revolutionized our understanding of the universe.
-            \`
-            </example>
-
-            Everything below is the actual data you will be working with. Good luck!
-
-            <query>
-            ${question}
-            </query>
-
-            <text>
-            ${doc.pageContent}
-            </text>
-
-            Make sure to answer the query in the summary.
-          `);
-
-              const document = new Document({
-                pageContent: res.content as string,
-                metadata: {
-                  title: doc.metadata.title,
-                  url: doc.metadata.url,
-                },
-              });
-
-              docs.push(document);
-            }),
-          );
-
-          return { query: question, docs: docs };
-        } else {
-          question = question.replace(/<think>.*?<\/think>/g, '');
-
-          const res = await searchSearxng(question, {
-            language: 'en',
-            engines: this.config.activeEngines,
-          });
-
-          const documents = res.results.map(
-            (result) =>
-              new Document({
-                pageContent:
-                  result.content ||
-                  (this.config.activeEngines.includes('youtube')
-                    ? result.title
-                    : '') /* Todo: Implement transcript grabbing using Youtubei (source: https://www.npmjs.com/package/youtubei) */,
-                metadata: {
-                  title: result.title,
-                  url: result.url,
-                  ...(result.img_src && { img_src: result.img_src }),
-                },
-              }),
-          );
-
-          return { query: question, docs: documents };
-        }
-      }),
-    ]);
-  }
-
-  private async createAnsweringChain(
-    llm: BaseChatModel,
-    fileIds: string[],
-    embeddings: Embeddings,
-    optimizationMode: 'speed' | 'balanced' | 'quality',
-    systemInstructions: string,
-  ) {
-    return RunnableSequence.from([
-      RunnableMap.from({
-        systemInstructions: () => systemInstructions,
-        query: (input: BasicChainInput) => input.query,
-        chat_history: (input: BasicChainInput) => input.chat_history,
-        date: () => new Date().toISOString(),
-        context: RunnableLambda.from(async (input: BasicChainInput) => {
-          const processedHistory = formatChatHistoryAsString(
-            input.chat_history,
-          );
-
-          let docs: Document[] | null = null;
-          let query = input.query;
-
-          if (this.config.searchWeb) {
-            const searchRetrieverChain =
-              await this.createSearchRetrieverChain(llm);
-
-            const searchRetrieverResult = await searchRetrieverChain.invoke({
-              chat_history: processedHistory,
-              query,
-            });
-
-            query = searchRetrieverResult.query;
-            docs = searchRetrieverResult.docs;
-          }
-
-          const sortedDocs = await this.rerankDocs(
-            query,
-            docs ?? [],
-            fileIds,
-            embeddings,
-            optimizationMode,
-          );
-
-          return sortedDocs;
-        })
-          .withConfig({
-            runName: 'FinalSourceRetriever',
-          })
-          .pipe(this.processDocs),
-      }),
-      ChatPromptTemplate.fromMessages([
-        ['system', this.config.responsePrompt],
-        new MessagesPlaceholder('chat_history'),
-        ['user', '{query}'],
-      ]),
-      llm,
-      this.strParser,
-    ]).withConfig({
-      runName: 'FinalResponseGenerator',
-    });
-  }
-
-  private async rerankDocs(
-    query: string,
-    docs: Document[],
-    fileIds: string[],
-    embeddings: Embeddings,
-    optimizationMode: 'speed' | 'balanced' | 'quality',
-  ) {
-    if (docs.length === 0 && fileIds.length === 0) {
-      return docs;
-    }
-
-    const filesData = fileIds
-      .map((file) => {
-        const filePath = path.join(process.cwd(), 'uploads', file);
-
-        const contentPath = filePath + '-extracted.json';
-        const embeddingsPath = filePath + '-embeddings.json';
-
-        const content = JSON.parse(fs.readFileSync(contentPath, 'utf8'));
-        const embeddings = JSON.parse(fs.readFileSync(embeddingsPath, 'utf8'));
-
-        const fileSimilaritySearchObject = content.contents.map(
-          (c: string, i: number) => {
-            return {
-              fileName: content.title,
-              content: c,
-              embeddings: embeddings.embeddings[i],
-            };
-          },
-        );
-
-        return fileSimilaritySearchObject;
-      })
-      .flat();
-
-    if (query.toLocaleLowerCase() === 'summarize') {
-      return docs.slice(0, 15);
-    }
-
-    const docsWithContent = docs.filter(
-      (doc) => doc.pageContent && doc.pageContent.length > 0,
-    );
-
-    if (optimizationMode === 'speed' || this.config.rerank === false) {
-      if (filesData.length > 0) {
-        const [queryEmbedding] = await Promise.all([
-          embeddings.embedQuery(query),
-        ]);
-
-        const fileDocs = filesData.map((fileData) => {
-          return new Document({
-            pageContent: fileData.content,
-            metadata: {
-              title: fileData.fileName,
-              url: `File`,
-            },
-          });
-        });
-
-        const similarity = filesData.map((fileData, i) => {
-          const sim = computeSimilarity(queryEmbedding, fileData.embeddings);
-
-          return {
-            index: i,
-            similarity: sim,
-          };
-        });
-
-        let sortedDocs = similarity
-          .filter(
-            (sim) => sim.similarity > (this.config.rerankThreshold ?? 0.3),
-          )
-          .sort((a, b) => b.similarity - a.similarity)
-          .slice(0, 15)
-          .map((sim) => fileDocs[sim.index]);
-
-        sortedDocs =
-          docsWithContent.length > 0 ? sortedDocs.slice(0, 8) : sortedDocs;
-
-        return [
-          ...sortedDocs,
-          ...docsWithContent.slice(0, 15 - sortedDocs.length),
-        ];
-      } else {
-        return docsWithContent.slice(0, 15);
-      }
-    } else if (optimizationMode === 'balanced') {
-      const [docEmbeddings, queryEmbedding] = await Promise.all([
-        embeddings.embedDocuments(
-          docsWithContent.map((doc) => doc.pageContent),
-        ),
-        embeddings.embedQuery(query),
-      ]);
-
-      docsWithContent.push(
-        ...filesData.map((fileData) => {
-          return new Document({
-            pageContent: fileData.content,
-            metadata: {
-              title: fileData.fileName,
-              url: `File`,
-            },
-          });
-        }),
-      );
-
-      docEmbeddings.push(...filesData.map((fileData) => fileData.embeddings));
-
-      const similarity = docEmbeddings.map((docEmbedding, i) => {
-        const sim = computeSimilarity(queryEmbedding, docEmbedding);
-
-        return {
-          index: i,
-          similarity: sim,
-        };
-      });
-
-      const sortedDocs = similarity
-        .filter((sim) => sim.similarity > (this.config.rerankThreshold ?? 0.3))
-        .sort((a, b) => b.similarity - a.similarity)
-        .slice(0, 15)
-        .map((sim) => docsWithContent[sim.index]);
-
-      return sortedDocs;
-    }
-
-    return [];
-  }
-
-  private processDocs(docs: Document[]) {
-    return docs
-      .map(
-        (_, index) =>
-          `${index + 1}. ${docs[index].metadata.title} ${docs[index].pageContent}`,
-      )
-      .join('\n');
-  }
-
-  private async handleStream(
-    stream: AsyncGenerator<StreamEvent, any, any>,
-    emitter: eventEmitter,
-  ) {
-    for await (const event of stream) {
-      if (
-        event.event === 'on_chain_end' &&
-        event.name === 'FinalSourceRetriever'
-      ) {
-        emitter.emit(
-          'data',
-          JSON.stringify({ type: 'sources', data: event.data.output }),
-        );
-      }
-      if (
-        event.event === 'on_chain_stream' &&
-        event.name === 'FinalResponseGenerator'
-      ) {
-        emitter.emit(
-          'data',
-          JSON.stringify({ type: 'response', data: event.data.chunk }),
-        );
-      }
-      if (
-        event.event === 'on_chain_end' &&
-        event.name === 'FinalResponseGenerator'
-      ) {
-        emitter.emit('end');
-      }
-    }
-  }
-
-  async searchAndAnswer(
-    message: string,
-    history: BaseMessage[],
-    llm: BaseChatModel,
-    embeddings: Embeddings,
-    optimizationMode: 'speed' | 'balanced' | 'quality',
-    fileIds: string[],
-    systemInstructions: string,
-  ) {
-    const emitter = new eventEmitter();
-
-    const answeringChain = await this.createAnsweringChain(
-      llm,
-      fileIds,
-      embeddings,
-      optimizationMode,
-      systemInstructions,
-    );
-
-    const stream = answeringChain.streamEvents(
-      {
-        chat_history: history,
-        query: message,
-      },
-      {
-        version: 'v1',
-      },
-    );
-
-    this.handleStream(stream, emitter);
-
-    return emitter;
-  }
-}
-
-export default MetaSearchAgent;

src/lib/session.ts

@@ -0,0 +1,82 @@
+import { EventEmitter } from 'stream';
+import { applyPatch } from 'rfc6902';
+import { Block } from './types';
+
+class SessionManager {
+  private static sessions = new Map<string, SessionManager>();
+  readonly id: string;
+  private blocks = new Map<string, Block>();
+  private events: { event: string; data: any }[] = [];
+  private emitter = new EventEmitter();
+  private TTL_MS = 30 * 60 * 1000;
+
+  constructor(id?: string) {
+    this.id = id ?? crypto.randomUUID();
+
+    setTimeout(() => {
+      SessionManager.sessions.delete(this.id);
+    }, this.TTL_MS);
+  }
+
+  static getSession(id: string): SessionManager | undefined {
+    return this.sessions.get(id);
+  }
+
+  static getAllSessions(): SessionManager[] {
+    return Array.from(this.sessions.values());
+  }
+
+  static createSession(): SessionManager {
+    const session = new SessionManager();
+    this.sessions.set(session.id, session);
+    return session;
+  }
+
+  removeAllListeners() {
+    this.emitter.removeAllListeners();
+  }
+
+  emit(event: string, data: any) {
+    this.emitter.emit(event, data);
+    this.events.push({ event, data });
+  }
+
+  emitBlock(block: Block) {
+    this.blocks.set(block.id, block);
+    this.emit('data', {
+      type: 'block',
+      block: block,
+    });
+  }
+
+  getBlock(blockId: string): Block | undefined {
+    return this.blocks.get(blockId);
+  }
+
+  updateBlock(blockId: string, patch: any[]) {
+    const block = this.blocks.get(blockId);
+
+    if (block) {
+      applyPatch(block, patch);
+      this.blocks.set(blockId, block);
+      this.emit('data', {
+        type: 'updateBlock',
+        blockId: blockId,
+        patch: patch,
+      });
+    }
+  }
+
+  addListener(event: string, listener: (data: any) => void) {
+    this.emitter.addListener(event, listener);
+  }
+
+  replay() {
+    for (const { event, data } of this.events) {
+      /* Using emitter directly to avoid infinite loop */
+      this.emitter.emit(event, data);
+    }
+  }
+}
+
+export default SessionManager;

src/lib/types.ts

@@ -1,9 +1,74 @@
-type Message = {
+export type ChatTurnMessage = {
   role: 'user' | 'assistant' | 'system';
   content: string;
 };
 
-type Chunk = {
+export type Chunk = {
   content: string;
   metadata: Record<string, any>;
 };
+
+export type TextBlock = {
+  id: string;
+  type: 'text';
+  data: string;
+};
+
+export type SourceBlock = {
+  id: string;
+  type: 'source';
+  data: Chunk[];
+};
+
+export type SuggestionBlock = {
+  id: string;
+  type: 'suggestion';
+  data: string[];
+};
+
+export type WidgetBlock = {
+  id: string;
+  type: 'widget';
+  data: {
+    widgetType: string;
+    params: Record<string, any>;
+  };
+};
+
+export type ReasoningResearchBlock = {
+  id: string;
+  type: 'reasoning';
+  reasoning: string;
+};
+
+export type SearchingResearchBlock = {
+  id: string;
+  type: 'searching';
+  searching: string[];
+};
+
+export type ReadingResearchBlock = {
+  id: string;
+  type: 'reading';
+  reading: Chunk[];
+};
+
+export type ResearchBlockSubStep =
+  | ReasoningResearchBlock
+  | SearchingResearchBlock
+  | ReadingResearchBlock;
+
+export type ResearchBlock = {
+  id: string;
+  type: 'research';
+  data: {
+    subSteps: ResearchBlockSubStep[];
+  };
+};
+
+export type Block =
+  | TextBlock
+  | SourceBlock
+  | SuggestionBlock
+  | WidgetBlock
+  | ResearchBlock;

src/lib/utils/documents.ts

@@ -1,99 +0,0 @@
-import axios from 'axios';
-import { htmlToText } from 'html-to-text';
-import { RecursiveCharacterTextSplitter } from '@langchain/textsplitters';
-import { Document } from '@langchain/core/documents';
-import pdfParse from 'pdf-parse';
-
-export const getDocumentsFromLinks = async ({ links }: { links: string[] }) => {
-  const splitter = new RecursiveCharacterTextSplitter();
-
-  let docs: Document[] = [];
-
-  await Promise.all(
-    links.map(async (link) => {
-      link =
-        link.startsWith('http://') || link.startsWith('https://')
-          ? link
-          : `https://${link}`;
-
-      try {
-        const res = await axios.get(link, {
-          responseType: 'arraybuffer',
-        });
-
-        const isPdf = res.headers['content-type'] === 'application/pdf';
-
-        if (isPdf) {
-          const pdfText = await pdfParse(res.data);
-          const parsedText = pdfText.text
-            .replace(/(\r\n|\n|\r)/gm, ' ')
-            .replace(/\s+/g, ' ')
-            .trim();
-
-          const splittedText = await splitter.splitText(parsedText);
-          const title = 'PDF Document';
-
-          const linkDocs = splittedText.map((text) => {
-            return new Document({
-              pageContent: text,
-              metadata: {
-                title: title,
-                url: link,
-              },
-            });
-          });
-
-          docs.push(...linkDocs);
-          return;
-        }
-
-        const parsedText = htmlToText(res.data.toString('utf8'), {
-          selectors: [
-            {
-              selector: 'a',
-              options: {
-                ignoreHref: true,
-              },
-            },
-          ],
-        })
-          .replace(/(\r\n|\n|\r)/gm, ' ')
-          .replace(/\s+/g, ' ')
-          .trim();
-
-        const splittedText = await splitter.splitText(parsedText);
-        const title = res.data
-          .toString('utf8')
-          .match(/<title.*>(.*?)<\/title>/)?.[1];
-
-        const linkDocs = splittedText.map((text) => {
-          return new Document({
-            pageContent: text,
-            metadata: {
-              title: title || link,
-              url: link,
-            },
-          });
-        });
-
-        docs.push(...linkDocs);
-      } catch (err) {
-        console.error(
-          'An error occurred while getting documents from links: ',
-          err,
-        );
-        docs.push(
-          new Document({
-            pageContent: `Failed to retrieve content from the link: ${err}`,
-            metadata: {
-              title: 'Failed to retrieve content',
-              url: link,
-            },
-          }),
-        );
-      }
-    }),
-  );
-
-  return docs;
-};

src/lib/utils/formatHistory.ts

@@ -1,10 +1,10 @@
-import { BaseMessage, isAIMessage } from '@langchain/core/messages';
+import { ChatTurnMessage } from '../types';
 
-const formatChatHistoryAsString = (history: BaseMessage[]) => {
+const formatChatHistoryAsString = (history: ChatTurnMessage[]) => {
   return history
     .map(
       (message) =>
-        `${isAIMessage(message) ? 'AI' : 'User'}: ${message.content}`,
+        `${message.role === 'assistant' ? 'AI' : 'User'}: ${message.content}`,
     )
     .join('\n');
 };

yarn.lock

@@ -24,7 +24,7 @@
   resolved "https://registry.yarnpkg.com/@babel/runtime/-/runtime-7.27.3.tgz#10491113799fb8d77e1d9273384d5d68deeea8f6"
   integrity sha512-7EYtGezsdiDMyY80+65EzwiGmcJqpmcZCojSXaRgdrBaGtWTgDZKq69cPIVped6MkIM78cTQ2GOiEYjwOlG4xw==
 
-"@babel/runtime@^7.18.3":
+"@babel/runtime@^7.18.3", "@babel/runtime@^7.26.10":
   version "7.28.4"
   resolved "https://registry.yarnpkg.com/@babel/runtime/-/runtime-7.28.4.tgz#a70226016fabe25c5783b2f22d3e1c9bc5ca3326"
   integrity sha512-Q/N6JNWvIvPnLDvjlE1OUBLPQHH6l3CltCEsHIujp45zQUSSh8K+gHnaEX45yAT1nyngnINhvWtzN+Nb9D8RAQ==
@@ -55,6 +55,19 @@
     enabled "2.0.x"
     kuler "^2.0.0"
 
+"@deno/shim-deno-test@^0.5.0":
+  version "0.5.0"
+  resolved "https://registry.yarnpkg.com/@deno/shim-deno-test/-/shim-deno-test-0.5.0.tgz#7d5dd221c736d182e587b8fd9bfca49b4dc0aa79"
+  integrity sha512-4nMhecpGlPi0cSzT67L+Tm+GOJqvuk8gqHBziqcUQOarnuIax1z96/gJHCSIz2Z0zhxE6Rzwb3IZXPtFh51j+w==
+
+"@deno/shim-deno@~0.18.0":
+  version "0.18.2"
+  resolved "https://registry.yarnpkg.com/@deno/shim-deno/-/shim-deno-0.18.2.tgz#9fe2fe7c91062bf2d127204f3110c09806cbef92"
+  integrity sha512-oQ0CVmOio63wlhwQF75zA4ioolPvOwAoK0yuzcS5bDC1JUvH3y1GS8xPh8EOpcoDQRU4FTG8OQfxhpR+c6DrzA==
+  dependencies:
+    "@deno/shim-deno-test" "^0.5.0"
+    which "^4.0.0"
+
 "@drizzle-team/brocli@^0.10.2":
   version "0.10.2"
   resolved "https://registry.yarnpkg.com/@drizzle-team/brocli/-/brocli-0.10.2.tgz#9757c006a43daaa6f45512e6cf5fabed36fb9da7"
@@ -1822,6 +1835,11 @@ commander@^4.0.0:
   resolved "https://registry.yarnpkg.com/commander/-/commander-4.1.1.tgz#9fd602bd936294e9e9ef46a3f4d6964044b18068"
   integrity sha512-NOKm8xhkzAjzFx8B2v5OAHT+u5pRQc2UCa2Vq9jYL/31o2wi9mxBA7LIFs3sV5VSC49z6pEhfbMULvShKj26WA==
 
+complex.js@^2.2.5:
+  version "2.4.3"
+  resolved "https://registry.yarnpkg.com/complex.js/-/complex.js-2.4.3.tgz#72ee9c303a9b89ebcfeca0d39f74927d38721fce"
+  integrity sha512-UrQVSUur14tNX6tiP4y8T4w4FeJAX3bi2cIv0pu/DTLFNxoq7z2Yh83Vfzztj6Px3X/lubqQ9IrPp7Bpn6p4MQ==
+
 compute-cosine-similarity@^1.1.0:
   version "1.1.0"
   resolved "https://registry.yarnpkg.com/compute-cosine-similarity/-/compute-cosine-similarity-1.1.0.tgz#0086a06b0239deb90f231f0da894efdc48884609"
@@ -1947,6 +1965,11 @@ decamelize@1.2.0:
   resolved "https://registry.yarnpkg.com/decamelize/-/decamelize-1.2.0.tgz#f6534d15148269b20352e7bee26f501f9a191290"
   integrity sha512-z2S+W9X73hAUUki+N+9Za2lBlun89zigOyGrsax+KUQ6wKW4ZoWpEYBkGhQjwAjjDCkWxhY0VKEhk8wzY7F5cA==
 
+decimal.js@^10.4.3:
+  version "10.6.0"
+  resolved "https://registry.yarnpkg.com/decimal.js/-/decimal.js-10.6.0.tgz#e649a43e3ab953a72192ff5983865e509f37ed9a"
+  integrity sha512-YpgQiITW3JXGntzdUmyUR1V812Hn8T1YVXhCu+wO3OpS4eU9l4YdD3qjyiKdV6mvV29zapkMeD390UVEf2lkUg==
+
 decompress-response@^6.0.0:
   version "6.0.0"
   resolved "https://registry.yarnpkg.com/decompress-response/-/decompress-response-6.0.0.tgz#ca387612ddb7e104bd16d85aab00d5ecf09c66fc"
@@ -2379,6 +2402,16 @@ escalade@^3.1.1:
   resolved "https://registry.yarnpkg.com/escalade/-/escalade-3.1.2.tgz#54076e9ab29ea5bf3d8f1ed62acffbb88272df27"
   integrity sha512-ErCHMCae19vR8vQGe50xIsVomy19rg6gFu3+r3jkEO46suLMWBksvVyoGgQV+jOfl84ZSOSlmv6Gxa89PmTGmA==
 
+escape-latex@^1.2.0:
+  version "1.2.0"
+  resolved "https://registry.yarnpkg.com/escape-latex/-/escape-latex-1.2.0.tgz#07c03818cf7dac250cce517f4fda1b001ef2bca1"
+  integrity sha512-nV5aVWW1K0wEiUIEdZ4erkGGH8mDxGyxSeqPzRNtWP7ataw+/olFObw7hujFWlVjNsaDFw5VZ5NzVSIqRgfTiw==
+
+escape-string-regexp@^1.0.2:
+  version "1.0.5"
+  resolved "https://registry.yarnpkg.com/escape-string-regexp/-/escape-string-regexp-1.0.5.tgz#1b61c0562190a8dff6ae3bb2cf0200ca130b86d4"
+  integrity sha512-vbRorB5FUQWvla16U8R/qgaFIya2qGzwDrNmCZuYKrbdSUMG6I1ZCGQRefkRVhuOkIGVne7BQ35DSfo1qvJqFg==
+
 escape-string-regexp@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/escape-string-regexp/-/escape-string-regexp-4.0.0.tgz#14ba83a5d373e3d311e5afca29cf5bfad965bf34"
@@ -2607,6 +2640,11 @@ expand-template@^2.0.3:
   resolved "https://registry.yarnpkg.com/expand-template/-/expand-template-2.0.3.tgz#6e14b3fcee0f3a6340ecb57d2e8918692052a47c"
   integrity sha512-XYfuKMvj4O35f/pOXLObndIRvyQ+/+6AhODh+OKWj9S9498pHHn/IMszH+gt0fBCRWMNfk1ZSp5x3AifmnI2vg==
 
+fancy-canvas@2.1.0:
+  version "2.1.0"
+  resolved "https://registry.yarnpkg.com/fancy-canvas/-/fancy-canvas-2.1.0.tgz#44b40e40419ad8ef8304df365e4276767e918552"
+  integrity sha512-nifxXJ95JNLFR2NgRV4/MxVP45G9909wJTEKz5fg/TZS20JJZA6hfgRVh/bC9bwl2zBtBNcYPjiBE4njQHVBwQ==
+
 fast-deep-equal@^3.1.1, fast-deep-equal@^3.1.3:
   version "3.1.3"
   resolved "https://registry.yarnpkg.com/fast-deep-equal/-/fast-deep-equal-3.1.3.tgz#3a7d56b559d6cbc3eb512325244e619a65c6c525"
@@ -2645,6 +2683,14 @@ fecha@^4.2.0:
   resolved "https://registry.yarnpkg.com/fecha/-/fecha-4.2.3.tgz#4d9ccdbc61e8629b259fdca67e65891448d569fd"
   integrity sha512-OP2IUU6HeYKJi3i0z4A19kHMQoLVs4Hc+DPqqxI2h/DPZHTm/vjsfC6P0b4jCMy14XizLBqvndQ+UilD7707Jw==
 
+"fetch-mock-cache@npm:fetch-mock-cache@^2.1.3":
+  version "2.3.1"
+  resolved "https://registry.yarnpkg.com/fetch-mock-cache/-/fetch-mock-cache-2.3.1.tgz#1018f5fc2f91cf2511abcea8a5e3a3b05e2d02bf"
+  integrity sha512-hDk+Nbt0Y8Aq7KTEU6ASQAcpB34UjhkpD3QjzD6yvEKP4xVElAqXrjQ7maL+LYMGafx51Zq6qUfDM57PNu/qMw==
+  dependencies:
+    debug "^4.3.4"
+    filenamify-url "2.1.2"
+
 fflate@^0.8.1:
   version "0.8.2"
   resolved "https://registry.yarnpkg.com/fflate/-/fflate-0.8.2.tgz#fc8631f5347812ad6028bbe4a2308b2792aa1dea"
@@ -2662,6 +2708,28 @@ file-uri-to-path@1.0.0:
   resolved "https://registry.yarnpkg.com/file-uri-to-path/-/file-uri-to-path-1.0.0.tgz#553a7b8446ff6f684359c445f1e37a05dacc33dd"
   integrity sha512-0Zt+s3L7Vf1biwWZ29aARiVYLx7iMGnEUl9x33fbB/j3jR81u/O2LbqK+Bm1CDSNDKVtJ/YjwY7TUd5SkeLQLw==
 
+filename-reserved-regex@^2.0.0:
+  version "2.0.0"
+  resolved "https://registry.yarnpkg.com/filename-reserved-regex/-/filename-reserved-regex-2.0.0.tgz#abf73dfab735d045440abfea2d91f389ebbfa229"
+  integrity sha512-lc1bnsSr4L4Bdif8Xb/qrtokGbq5zlsms/CYH8PP+WtCkGNF65DPiQY8vG3SakEdRn8Dlnm+gW/qWKKjS5sZzQ==
+
+filenamify-url@2.1.2:
+  version "2.1.2"
+  resolved "https://registry.yarnpkg.com/filenamify-url/-/filenamify-url-2.1.2.tgz#844607d5e86919617340ba0fad4b458dae247100"
+  integrity sha512-3rMbAr7vDNMOGsj1aMniQFl749QjgM+lMJ/77ZRSPTIgxvolZwoQbn8dXLs7xfd+hAdli+oTnSWZNkJJLWQFEQ==
+  dependencies:
+    filenamify "^4.3.0"
+    humanize-url "^2.1.1"
+
+filenamify@^4.3.0:
+  version "4.3.0"
+  resolved "https://registry.yarnpkg.com/filenamify/-/filenamify-4.3.0.tgz#62391cb58f02b09971c9d4f9d63b3cf9aba03106"
+  integrity sha512-hcFKyUG57yWGAzu1CMt/dPzYZuv+jAJUT85bL8mrXvNe6hWj6yEHEc4EdcgiA6Z3oi1/9wXJdZPXF2dZNgwgOg==
+  dependencies:
+    filename-reserved-regex "^2.0.0"
+    strip-outer "^1.0.1"
+    trim-repeated "^1.0.0"
+
 fill-range@^7.0.1:
   version "7.0.1"
   resolved "https://registry.yarnpkg.com/fill-range/-/fill-range-7.0.1.tgz#1919a6a7c75fe38b2c7c77e5198535da9acdda40"
@@ -2764,6 +2832,11 @@ fraction.js@^4.3.7:
   resolved "https://registry.yarnpkg.com/fraction.js/-/fraction.js-4.3.7.tgz#06ca0085157e42fda7f9e726e79fefc4068840f7"
   integrity sha512-ZsDfxO51wGAXREY55a7la9LScWpwv9RxIrYABrlvOFBlH/ShPnrtsXeuUIfXKKOVicNxQ+o8JTbJvjS4M89yew==
 
+fraction.js@^5.2.1:
+  version "5.3.4"
+  resolved "https://registry.yarnpkg.com/fraction.js/-/fraction.js-5.3.4.tgz#8c0fcc6a9908262df4ed197427bdeef563e0699a"
+  integrity sha512-1X1NTtiJphryn/uLQz3whtY6jK3fTqoE3ohKs0tT+Ujr1W59oopxmoEh7Lu5p6vBaPbgoM0bzveAW4Qi5RyWDQ==
+
 framer-motion@^12.23.24:
   version "12.23.24"
   resolved "https://registry.yarnpkg.com/framer-motion/-/framer-motion-12.23.24.tgz#4895b67e880bd2b1089e61fbaa32ae802fc24b8c"
@@ -3111,6 +3184,13 @@ humanize-ms@^1.2.1:
   dependencies:
     ms "^2.0.0"
 
+humanize-url@^2.1.1:
+  version "2.1.1"
+  resolved "https://registry.yarnpkg.com/humanize-url/-/humanize-url-2.1.1.tgz#1be3dc2b8a23ee28fdf9db95b22962b3eb5e4683"
+  integrity sha512-V4nxsPGNE7mPjr1qDp471YfW8nhBiTRWrG/4usZlpvFU8I7gsV7Jvrrzv/snbLm5dWO3dr1ennu2YqnhTWFmYA==
+  dependencies:
+    normalize-url "^4.5.1"
+
 ieee754@^1.1.13:
   version "1.2.1"
   resolved "https://registry.yarnpkg.com/ieee754/-/ieee754-1.2.1.tgz#8eb7a10a63fff25d15a57b001586d177d1b0d352"
@@ -3398,6 +3478,11 @@ jackspeak@^2.3.5, jackspeak@^2.3.6:
   optionalDependencies:
     "@pkgjs/parseargs" "^0.11.0"
 
+javascript-natural-sort@^0.7.1:
+  version "0.7.1"
+  resolved "https://registry.yarnpkg.com/javascript-natural-sort/-/javascript-natural-sort-0.7.1.tgz#f9e2303d4507f6d74355a73664d1440fb5a0ef59"
+  integrity sha512-nO6jcEfZWQXDhOiBtG2KvKyEptz7RVbpGP4vTD2hLBdmNQSsCiicO2Ioinv6UI4y9ukqnBpy+XZ9H6uLNgJTlw==
+
 jiti@^1.21.0:
   version "1.21.0"
   resolved "https://registry.yarnpkg.com/jiti/-/jiti-1.21.0.tgz#7c97f8fe045724e136a397f7340475244156105d"
@@ -3440,6 +3525,11 @@ json-schema-traverse@^0.4.1:
   resolved "https://registry.yarnpkg.com/json-schema-traverse/-/json-schema-traverse-0.4.1.tgz#69f6a87d9513ab8bb8fe63bdb0979c448e684660"
   integrity sha512-xbbCH5dCYU5T8LcEhhuh7HJ88HXuW3qsI3Y0zOZFKfZEHcpWiHU/Jxzk629Brsab/mMiHQti9wMP+845RPe3Vg==
 
+json-schema@^0.4.0:
+  version "0.4.0"
+  resolved "https://registry.yarnpkg.com/json-schema/-/json-schema-0.4.0.tgz#f7de4cf6efab838ebaeb3236474cbba5a1930ab5"
+  integrity sha512-es94M3nTIfsEPisRafak+HDLfHXnKBhV3vU5eqPcS3flIWqcxJWgXHXiey3YrpaNsanY5ei1VoYEbOzijuq9BA==
+
 json-stable-stringify-without-jsonify@^1.0.1:
   version "1.0.1"
   resolved "https://registry.yarnpkg.com/json-stable-stringify-without-jsonify/-/json-stable-stringify-without-jsonify-1.0.1.tgz#9db7b59496ad3f3cfef30a75142d2d930ad72651"
@@ -3578,6 +3668,13 @@ lie@~3.3.0:
   dependencies:
     immediate "~3.0.5"
 
+lightweight-charts@^5.0.9:
+  version "5.0.9"
+  resolved "https://registry.yarnpkg.com/lightweight-charts/-/lightweight-charts-5.0.9.tgz#22ccaf5643b4561c0accecee5d84eec78d3d058d"
+  integrity sha512-8oQIis8jfZVfSwz8j9Z5x3O79dIRTkEYI9UY7DKtE4O3ZxlHjMK3L0+4nOVOOFq4FHI/oSIzz1RHeNImCk6/Jg==
+  dependencies:
+    fancy-canvas "2.1.0"
+
 lilconfig@^2.1.0:
   version "2.1.0"
   resolved "https://registry.yarnpkg.com/lilconfig/-/lilconfig-2.1.0.tgz#78e23ac89ebb7e1bfbf25b18043de756548e7f52"
@@ -3703,6 +3800,21 @@ math-intrinsics@^1.1.0:
   resolved "https://registry.yarnpkg.com/math-intrinsics/-/math-intrinsics-1.1.0.tgz#a0dd74be81e2aa5c2f27e65ce283605ee4e2b7f9"
   integrity sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g==
 
+mathjs@^15.1.0:
+  version "15.1.0"
+  resolved "https://registry.yarnpkg.com/mathjs/-/mathjs-15.1.0.tgz#e910f626c5d66ff1902eb69c3b2e7b7d010fc39e"
+  integrity sha512-HfnAcScQm9drGryodlDqeS3WAl4gUTYGDcOtcqL/8s23MZ28Ib1i8XnYK3ZdjNuaW/L4BAp9lIp8vxAMrcuu1w==
+  dependencies:
+    "@babel/runtime" "^7.26.10"
+    complex.js "^2.2.5"
+    decimal.js "^10.4.3"
+    escape-latex "^1.2.0"
+    fraction.js "^5.2.1"
+    javascript-natural-sort "^0.7.1"
+    seedrandom "^3.0.5"
+    tiny-emitter "^2.1.0"
+    typed-function "^4.2.1"
+
 merge2@^1.3.0, merge2@^1.4.1:
   version "1.4.1"
   resolved "https://registry.yarnpkg.com/merge2/-/merge2-1.4.1.tgz#4368892f885e907455a6fd7dc55c0c9d404990ae"
@@ -3909,6 +4021,11 @@ normalize-range@^0.1.2:
   resolved "https://registry.yarnpkg.com/normalize-range/-/normalize-range-0.1.2.tgz#2d10c06bdfd312ea9777695a4d28439456b75942"
   integrity sha512-bdok/XvKII3nUpklnV6P2hxtMNrCboOjAcyBuQnWEhO665FwrSNRxU+AqpsyvO6LgGYPspN+lu5CLtw4jPRKNA==
 
+normalize-url@^4.5.1:
+  version "4.5.1"
+  resolved "https://registry.yarnpkg.com/normalize-url/-/normalize-url-4.5.1.tgz#0dd90cf1288ee1d1313b87081c9a5932ee48518a"
+  integrity sha512-9UZCFRHQdNrfTpGg8+1INIg93B6zE0aXMVFkw1WFwvO4SlZywU6aLg5Of0Ap/PgcbSw4LNxvMWXMeugwMCX0AA==
+
 object-assign@^4.0.1, object-assign@^4.1.1:
   version "4.1.1"
   resolved "https://registry.yarnpkg.com/object-assign/-/object-assign-4.1.1.tgz#2109adc7965887cfc05cbbd442cac8bfbb360863"
@@ -3992,6 +4109,13 @@ ollama@^0.5.12:
   dependencies:
     whatwg-fetch "^3.6.20"
 
+ollama@^0.6.3:
+  version "0.6.3"
+  resolved "https://registry.yarnpkg.com/ollama/-/ollama-0.6.3.tgz#b188573dd0ccb3b4759c1f8fa85067cb17f6673c"
+  integrity sha512-KEWEhIqE5wtfzEIZbDCLH51VFZ6Z3ZSa6sIOg/E/tBV8S51flyqBOXi+bRxlOYKDf8i327zG9eSTb8IJxvm3Zg==
+  dependencies:
+    whatwg-fetch "^3.6.20"
+
 once@^1.3.0, once@^1.3.1, once@^1.4.0:
   version "1.4.0"
   resolved "https://registry.yarnpkg.com/once/-/once-1.4.0.tgz#583b1aa775961d4b113ac17d9c50baef9dd76bd1"
@@ -4126,6 +4250,11 @@ parseley@^0.12.0:
     leac "^0.6.0"
     peberminta "^0.9.0"
 
+partial-json@^0.1.7:
+  version "0.1.7"
+  resolved "https://registry.yarnpkg.com/partial-json/-/partial-json-0.1.7.tgz#b735a89edb3e25f231a3c4caeaae71dc9f578605"
+  integrity sha512-Njv/59hHaokb/hRUjce3Hdv12wd60MtM9Z5Olmn+nehe0QDAsRtRbJPvJ0Z91TusF0SuZRIvnM+S4l6EIP8leA==
+
 path-exists@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/path-exists/-/path-exists-4.0.0.tgz#513bdbe2d3b95d7762e8c1137efa195c6c61b5b3"
@@ -4342,6 +4471,13 @@ proxy-from-env@^1.1.0:
   resolved "https://registry.yarnpkg.com/proxy-from-env/-/proxy-from-env-1.1.0.tgz#e102f16ca355424865755d2c9e8ea4f24d58c3e2"
   integrity sha512-D+zkORCbA9f1tdWRK0RaCR3GPv50cMxcrz4X8k5LTSUD1Dkw47mKJEZQNunItRTkWwgtaUSo1RVFRIG9ZXiFYg==
 
+psl@^1.1.33:
+  version "1.15.0"
+  resolved "https://registry.yarnpkg.com/psl/-/psl-1.15.0.tgz#bdace31896f1d97cec6a79e8224898ce93d974c6"
+  integrity sha512-JZd3gMVBAVQkSs6HdNZo9Sdo0LNcQeMNP3CozBJb3JYC/QUYZTnKxP+f8oWRX4rHP5EurWxqAHTSwUCjlNKa1w==
+  dependencies:
+    punycode "^2.3.1"
+
 pump@^3.0.0:
   version "3.0.2"
   resolved "https://registry.yarnpkg.com/pump/-/pump-3.0.2.tgz#836f3edd6bc2ee599256c924ffe0d88573ddcbf8"
@@ -4350,11 +4486,16 @@ pump@^3.0.0:
     end-of-stream "^1.1.0"
     once "^1.3.1"
 
-punycode@^2.1.0:
+punycode@^2.1.0, punycode@^2.1.1, punycode@^2.3.1:
   version "2.3.1"
   resolved "https://registry.yarnpkg.com/punycode/-/punycode-2.3.1.tgz#027422e2faec0b25e1549c3e1bd8309b9133b6e5"
   integrity sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg==
 
+querystringify@^2.1.1:
+  version "2.2.0"
+  resolved "https://registry.yarnpkg.com/querystringify/-/querystringify-2.2.0.tgz#3345941b4153cb9d082d8eee4cda2016a9aef7f6"
+  integrity sha512-FIqgj2EUvTa7R50u0rGsyTftzjYmv/a3hO345bZNrqabNqjtgiDMgmo4mkUjd+nzU5oF3dClKqFIPUKybUyqoQ==
+
 queue-microtask@^1.2.2:
   version "1.2.3"
   resolved "https://registry.yarnpkg.com/queue-microtask/-/queue-microtask-1.2.3.tgz#4929228bbc724dfac43e0efb058caf7b6cfb6243"
@@ -4480,6 +4621,11 @@ regexp.prototype.flags@^1.5.2:
     es-errors "^1.3.0"
     set-function-name "^2.0.1"
 
+requires-port@^1.0.0:
+  version "1.0.0"
+  resolved "https://registry.yarnpkg.com/requires-port/-/requires-port-1.0.0.tgz#925d2601d39ac485e091cf0da5c6e694dc3dcaff"
+  integrity sha512-KigOCHcocU3XODJxsu8i/j8T9tzT4adHiecwORRQ0ZZFcp7ahwXuRU1m+yuO90C5ZUyGeGfocHDI14M3L3yDAQ==
+
 resolve-from@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/resolve-from/-/resolve-from-4.0.0.tgz#4abcd852ad32dd7baabfe9b40e00a36db5f392e6"
@@ -4518,6 +4664,11 @@ reusify@^1.0.4:
   resolved "https://registry.yarnpkg.com/reusify/-/reusify-1.0.4.tgz#90da382b1e126efc02146e90845a88db12925d76"
   integrity sha512-U9nH88a3fc/ekCF1l0/UP1IosiuIjyTh7hBvXVMHYgVcfGvt897Xguj2UOLDeI5BG2m7/uwyaLVT6fbtCwTyzw==
 
+rfc6902@^5.1.2:
+  version "5.1.2"
+  resolved "https://registry.yarnpkg.com/rfc6902/-/rfc6902-5.1.2.tgz#774262ba7b032ab9abf9eb8e0312927e8f425062"
+  integrity sha512-zxcb+PWlE8PwX0tiKE6zP97THQ8/lHmeiwucRrJ3YFupWEmp25RmFSlB1dNTqjkovwqG4iq+u1gzJMBS3um8mA==
+
 rgbcolor@^1.0.1:
   version "1.0.1"
   resolved "https://registry.yarnpkg.com/rgbcolor/-/rgbcolor-1.0.1.tgz#d6505ecdb304a6595da26fa4b43307306775945d"
@@ -4590,6 +4741,11 @@ scheduler@^0.23.0:
   dependencies:
     loose-envify "^1.1.0"
 
+seedrandom@^3.0.5:
+  version "3.0.5"
+  resolved "https://registry.yarnpkg.com/seedrandom/-/seedrandom-3.0.5.tgz#54edc85c95222525b0c7a6f6b3543d8e0b3aa0a7"
+  integrity sha512-8OwmbklUNzwezjGInmZ+2clQmExQPvomqjL7LFqOYqtmuxRgQYqOD3mHaU+MvZn5FLUeVxVfQjwLZW/n/JFuqg==
+
 selderee@^0.11.0:
   version "0.11.0"
   resolved "https://registry.yarnpkg.com/selderee/-/selderee-0.11.0.tgz#6af0c7983e073ad3e35787ffe20cefd9daf0ec8a"
@@ -4958,6 +5114,13 @@ strip-json-comments@~2.0.1:
   resolved "https://registry.yarnpkg.com/strip-json-comments/-/strip-json-comments-2.0.1.tgz#3c531942e908c2697c0ec344858c286c7ca0a60a"
   integrity sha512-4gB8na07fecVVkOI6Rs4e7T6NOTki5EmL7TUduTs6bu3EdnSycntVJ4re8kgZA+wx9IueI2Y11bfbgwtzuE0KQ==
 
+strip-outer@^1.0.1:
+  version "1.0.1"
+  resolved "https://registry.yarnpkg.com/strip-outer/-/strip-outer-1.0.1.tgz#b2fd2abf6604b9d1e6013057195df836b8a9d631"
+  integrity sha512-k55yxKHwaXnpYGsOzg4Vl8+tDrWylxDEpknGjhTiZB8dFRU5rTo9CAzeycivxV3s+zlTKwrs6WxMxR95n26kwg==
+  dependencies:
+    escape-string-regexp "^1.0.2"
+
 styled-jsx@5.1.6:
   version "5.1.6"
   resolved "https://registry.yarnpkg.com/styled-jsx/-/styled-jsx-5.1.6.tgz#83b90c077e6c6a80f7f5e8781d0f311b2fe41499"
@@ -5103,6 +5266,23 @@ thenify-all@^1.0.0:
   dependencies:
     any-promise "^1.0.0"
 
+tiny-emitter@^2.1.0:
+  version "2.1.0"
+  resolved "https://registry.yarnpkg.com/tiny-emitter/-/tiny-emitter-2.1.0.tgz#1d1a56edfc51c43e863cbb5382a72330e3555423"
+  integrity sha512-NB6Dk1A9xgQPMoGqC5CVXn123gWyte215ONT5Pp5a0yt4nlEoO1ZWeCwpncaekPHXO60i47ihFnZPiRPjRMq4Q==
+
+tldts-core@^6.1.86:
+  version "6.1.86"
+  resolved "https://registry.yarnpkg.com/tldts-core/-/tldts-core-6.1.86.tgz#a93e6ed9d505cb54c542ce43feb14c73913265d8"
+  integrity sha512-Je6p7pkk+KMzMv2XXKmAE3McmolOQFdxkKw0R8EYNr7sELW46JqnNeTX8ybPiQgvg1ymCoF8LXs5fzFaZvJPTA==
+
+tldts@^6.1.32:
+  version "6.1.86"
+  resolved "https://registry.yarnpkg.com/tldts/-/tldts-6.1.86.tgz#087e0555b31b9725ee48ca7e77edc56115cd82f7"
+  integrity sha512-WMi/OQ2axVTf/ykqCQgXiIct+mSQDFdH2fkwhPwgEwvJ1kSzZRiinb0zF2Xb8u4+OqPChmyI6MEu4EezNJz+FQ==
+  dependencies:
+    tldts-core "^6.1.86"
+
 to-regex-range@^5.0.1:
   version "5.0.1"
   resolved "https://registry.yarnpkg.com/to-regex-range/-/to-regex-range-5.0.1.tgz#1648c44aae7c8d988a326018ed72f5b4dd0392e4"
@@ -5110,11 +5290,42 @@ to-regex-range@^5.0.1:
   dependencies:
     is-number "^7.0.0"
 
+"tough-cookie-file-store@npm:tough-cookie-file-store@^2.0.3":
+  version "2.0.3"
+  resolved "https://registry.yarnpkg.com/tough-cookie-file-store/-/tough-cookie-file-store-2.0.3.tgz#788f7a6fe5cd8f61a1afb71b2f0b964ebf914b80"
+  integrity sha512-sMpZVcmFf6EYFHFFl+SYH4W1/OnXBYMGDsv2IlbQ2caHyFElW/UR/gpj/KYU1JwmP4dE9xqwv2+vWcmlXHojSw==
+  dependencies:
+    tough-cookie "^4.0.0"
+
+tough-cookie@^4.0.0:
+  version "4.1.4"
+  resolved "https://registry.yarnpkg.com/tough-cookie/-/tough-cookie-4.1.4.tgz#945f1461b45b5a8c76821c33ea49c3ac192c1b36"
+  integrity sha512-Loo5UUvLD9ScZ6jh8beX1T6sO1w2/MpCRpEP7V280GKMVUQ0Jzar2U3UJPsrdbziLEMMhu3Ujnq//rhiFuIeag==
+  dependencies:
+    psl "^1.1.33"
+    punycode "^2.1.1"
+    universalify "^0.2.0"
+    url-parse "^1.5.3"
+
+"tough-cookie@npm:tough-cookie@^5.1.1":
+  version "5.1.2"
+  resolved "https://registry.yarnpkg.com/tough-cookie/-/tough-cookie-5.1.2.tgz#66d774b4a1d9e12dc75089725af3ac75ec31bed7"
+  integrity sha512-FVDYdxtnj0G6Qm/DhNPSb8Ju59ULcup3tuJxkFb5K8Bv2pUXILbf0xZWU8PX8Ov19OXljbUyveOFwRMwkXzO+A==
+  dependencies:
+    tldts "^6.1.32"
+
 tr46@~0.0.3:
   version "0.0.3"
   resolved "https://registry.yarnpkg.com/tr46/-/tr46-0.0.3.tgz#8184fd347dac9cdc185992f3a6622e14b9d9ab6a"
   integrity sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==
 
+trim-repeated@^1.0.0:
+  version "1.0.0"
+  resolved "https://registry.yarnpkg.com/trim-repeated/-/trim-repeated-1.0.0.tgz#e3646a2ea4e891312bf7eace6cfb05380bc01c21"
+  integrity sha512-pkonvlKk8/ZuR0D5tLW8ljt5I8kmxp2XKymhepUeOdCEfKpZaktSArkLHZt76OB1ZvO9bssUsDty4SWhLvZpLg==
+  dependencies:
+    escape-string-regexp "^1.0.2"
+
 triple-beam@^1.3.0:
   version "1.4.1"
   resolved "https://registry.yarnpkg.com/triple-beam/-/triple-beam-1.4.1.tgz#6fde70271dc6e5d73ca0c3b24e2d92afb7441984"
@@ -5218,6 +5429,11 @@ typed-array-length@^1.0.6:
     is-typed-array "^1.1.13"
     possible-typed-array-names "^1.0.0"
 
+typed-function@^4.2.1:
+  version "4.2.1"
+  resolved "https://registry.yarnpkg.com/typed-function/-/typed-function-4.2.1.tgz#19aa51847aa2dea9ef5e7fb7641c060179a74426"
+  integrity sha512-EGjWssW7Tsk4DGfE+5yluuljS1OGYWiI1J6e8puZz9nTMM51Oug8CD5Zo4gWMsOhq5BI+1bF+rWTm4Vbj3ivRA==
+
 typescript@^5.9.3:
   version "5.9.3"
   resolved "https://registry.yarnpkg.com/typescript/-/typescript-5.9.3.tgz#5b4f59e15310ab17a216f5d6cf53ee476ede670f"
@@ -5258,6 +5474,11 @@ undici-types@~7.14.0:
   resolved "https://registry.yarnpkg.com/undici-types/-/undici-types-7.14.0.tgz#4c037b32ca4d7d62fae042174604341588bc0840"
   integrity sha512-QQiYxHuyZ9gQUIrmPo3IA+hUl4KYk8uSA7cHrcKd/l3p1OTpZcM0Tbp9x7FAtXdAYhlasd60ncPpgu6ihG6TOA==
 
+universalify@^0.2.0:
+  version "0.2.0"
+  resolved "https://registry.yarnpkg.com/universalify/-/universalify-0.2.0.tgz#6451760566fa857534745ab1dde952d1b1761be0"
+  integrity sha512-CJ1QgKmNg3CwvAv/kOFmtnEN05f0D/cn9QntgNOQlQF9dgvVTHj3t+8JPdjqawCHk7V/KA+fbUqzZ9XWhcqPUg==
+
 update-browserslist-db@^1.0.13:
   version "1.0.13"
   resolved "https://registry.yarnpkg.com/update-browserslist-db/-/update-browserslist-db-1.0.13.tgz#3c5e4f5c083661bd38ef64b6328c26ed6c8248c4"
@@ -5273,6 +5494,14 @@ uri-js@^4.2.2:
   dependencies:
     punycode "^2.1.0"
 
+url-parse@^1.5.3:
+  version "1.5.10"
+  resolved "https://registry.yarnpkg.com/url-parse/-/url-parse-1.5.10.tgz#9d3c2f736c1d75dd3bd2be507dcc111f1e2ea9c1"
+  integrity sha512-WypcfiRhfeUP9vvF0j6rw0J3hrWrw6iZv3+22h6iRMJ/8z1Tj6XfLP4DsUix5MhMPnXpiHDoKyoZ/bdCkwBCiQ==
+  dependencies:
+    querystringify "^2.1.1"
+    requires-port "^1.0.0"
+
 use-composed-ref@^1.3.0:
   version "1.3.0"
   resolved "https://registry.yarnpkg.com/use-composed-ref/-/use-composed-ref-1.3.0.tgz#3d8104db34b7b264030a9d916c5e94fbe280dbda"
@@ -5473,6 +5702,17 @@ xmlbuilder@^10.0.0:
   resolved "https://registry.yarnpkg.com/xmlbuilder/-/xmlbuilder-10.1.1.tgz#8cae6688cc9b38d850b7c8d3c0a4161dcaf475b0"
   integrity sha512-OyzrcFLL/nb6fMGHbiRDuPup9ljBycsdCypwuyg5AAHvyWzGfChJpCXMG88AGTIMFhGZ9RccFN1e6lhg3hkwKg==
 
+yahoo-finance2@^3.10.2:
+  version "3.10.2"
+  resolved "https://registry.yarnpkg.com/yahoo-finance2/-/yahoo-finance2-3.10.2.tgz#ed1fbcb7cd0e5c37abe84936826aaca451739297"
+  integrity sha512-MH4EdugRurygLTMd1UryPwfYR8aWSOeyh++JSarMrf+bROfvNGmE0lAi/C9TuTc3mH8ORuRdt+O9PEeCCmzTLg==
+  dependencies:
+    "@deno/shim-deno" "~0.18.0"
+    fetch-mock-cache "npm:fetch-mock-cache@^2.1.3"
+    json-schema "^0.4.0"
+    tough-cookie "npm:tough-cookie@^5.1.1"
+    tough-cookie-file-store "npm:tough-cookie-file-store@^2.0.3"
+
 yallist@^4.0.0:
   version "4.0.0"
   resolved "https://registry.yarnpkg.com/yallist/-/yallist-4.0.0.tgz#9bb92790d9c0effec63be73519e11a35019a3a72"