Merge branch 'pr/703'

feat(models): Update Gemini chat models

docs/API/SEARCH.md

@@ -32,7 +32,8 @@ The API accepts a JSON object in the request body, where you define the focus mo
   "history": [
     ["human", "Hi, how are you?"],
     ["assistant", "I am doing well, how can I help you today?"]
-  ]
+  ],
+  "stream": false
 }
 ```
 
@@ -71,11 +72,13 @@ The API accepts a JSON object in the request body, where you define the focus mo
   ]
   ```
 
+- **`stream`** (boolean, optional): When set to `true`, enables streaming responses. Default is `false`.
+
 ### Response
 
 The response from the API includes both the final message and the sources used to generate that message.
 
-#### Example Response
+#### Standard Response (stream: false)
 
 ```json
 {
@@ -100,6 +103,28 @@ The response from the API includes both the final message and the sources used t
 }
 ```
 
+#### Streaming Response (stream: true)
+
+When streaming is enabled, the API returns a stream of newline-delimited JSON objects. Each line contains a complete, valid JSON object. The response has Content-Type: application/json.
+
+Example of streamed response objects:
+
+```
+{"type":"init","data":"Stream connected"}
+{"type":"sources","data":[{"pageContent":"...","metadata":{"title":"...","url":"..."}},...]}
+{"type":"response","data":"Perplexica is an "}
+{"type":"response","data":"innovative, open-source "}
+{"type":"response","data":"AI-powered search engine..."}
+{"type":"done"}
+```
+
+Clients should process each line as a separate JSON object. The different message types include:
+
+- **`init`**: Initial connection message
+- **`sources`**: All sources used for the response
+- **`response`**: Chunks of the generated answer text
+- **`done`**: Indicates the stream is complete
+
 ### Fields in the Response
 
 - **`message`** (string): The search result, generated based on the query and focus mode.

package.json

@@ -1,6 +1,6 @@
 {
   "name": "perplexica-frontend",
-  "version": "1.10.0",
+  "version": "1.10.1",
   "license": "MIT",
   "author": "ItzCrazyKns",
   "scripts": {
@@ -15,8 +15,10 @@
     "@headlessui/react": "^2.2.0",
     "@iarna/toml": "^2.2.5",
     "@icons-pack/react-simple-icons": "^12.3.0",
+    "@langchain/anthropic": "^0.3.15",
     "@langchain/community": "^0.3.36",
     "@langchain/core": "^0.3.42",
+    "@langchain/google-genai": "^0.1.12",
     "@langchain/openai": "^0.0.25",
     "@langchain/textsplitters": "^0.1.0",
     "@tailwindcss/typography": "^0.5.12",

src/app/api/chat/route.ts

@@ -295,9 +295,9 @@ export const POST = async (req: Request) => {
       },
     });
   } catch (err) {
-    console.error('An error ocurred while processing chat request:', err);
+    console.error('An error occurred while processing chat request:', err);
     return Response.json(
-      { message: 'An error ocurred while processing chat request' },
+      { message: 'An error occurred while processing chat request' },
       { status: 500 },
     );
   }

src/app/api/config/route.ts

@@ -59,9 +59,9 @@ export const GET = async (req: Request) => {
 
     return Response.json({ ...config }, { status: 200 });
   } catch (err) {
-    console.error('An error ocurred while getting config:', err);
+    console.error('An error occurred while getting config:', err);
     return Response.json(
-      { message: 'An error ocurred while getting config' },
+      { message: 'An error occurred while getting config' },
       { status: 500 },
     );
   }
@@ -100,9 +100,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ message: 'Config updated' }, { status: 200 });
   } catch (err) {
-    console.error('An error ocurred while updating config:', err);
+    console.error('An error occurred while updating config:', err);
     return Response.json(
-      { message: 'An error ocurred while updating config' },
+      { message: 'An error occurred while updating config' },
       { status: 500 },
     );
   }

src/app/api/discover/route.ts

@@ -48,7 +48,7 @@ export const GET = async (req: Request) => {
       },
     );
   } catch (err) {
-    console.error(`An error ocurred in discover route: ${err}`);
+    console.error(`An error occurred in discover route: ${err}`);
     return Response.json(
       {
         message: 'An error has occurred',

src/app/api/images/route.ts

@@ -74,9 +74,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ images }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while searching images: ${err}`);
+    console.error(`An error occurred while searching images: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while searching images' },
+      { message: 'An error occurred while searching images' },
       { status: 500 },
     );
   }

src/app/api/models/route.ts

@@ -34,7 +34,7 @@ export const GET = async (req: Request) => {
       },
     );
   } catch (err) {
-    console.error('An error ocurred while fetching models', err);
+    console.error('An error occurred while fetching models', err);
     return Response.json(
       {
         message: 'An error has occurred.',

src/app/api/search/route.ts

@@ -33,6 +33,7 @@ interface ChatRequestBody {
   embeddingModel?: embeddingModel;
   query: string;
   history: Array<[string, string]>;
+  stream?: boolean;
 }
 
 export const POST = async (req: Request) => {
@@ -48,6 +49,7 @@ export const POST = async (req: Request) => {
 
     body.history = body.history || [];
     body.optimizationMode = body.optimizationMode || 'balanced';
+    body.stream = body.stream || false;
 
     const history: BaseMessage[] = body.history.map((msg) => {
       return msg[0] === 'human'
@@ -125,40 +127,137 @@ export const POST = async (req: Request) => {
       [],
     );
 
-    return new Promise(
-      (
-        resolve: (value: Response) => void,
-        reject: (value: Response) => void,
-      ) => {
-        let message = '';
+    if (!body.stream) {
+      return new Promise(
+        (
+          resolve: (value: Response) => void,
+          reject: (value: Response) => void,
+        ) => {
+          let message = '';
+          let sources: any[] = [];
+
+          emitter.on('data', (data: string) => {
+            try {
+              const parsedData = JSON.parse(data);
+              if (parsedData.type === 'response') {
+                message += parsedData.data;
+              } else if (parsedData.type === 'sources') {
+                sources = parsedData.data;
+              }
+            } catch (error) {
+              reject(
+                Response.json(
+                  { message: 'Error parsing data' },
+                  { status: 500 },
+                ),
+              );
+            }
+          });
+
+          emitter.on('end', () => {
+            resolve(Response.json({ message, sources }, { status: 200 }));
+          });
+
+          emitter.on('error', (error: any) => {
+            reject(
+              Response.json(
+                { message: 'Search error', error },
+                { status: 500 },
+              ),
+            );
+          });
+        },
+      );
+    }
+
+    const encoder = new TextEncoder();
+
+    const abortController = new AbortController();
+    const { signal } = abortController;
+
+    const stream = new ReadableStream({
+      start(controller) {
         let sources: any[] = [];
 
-        emitter.on('data', (data) => {
+        controller.enqueue(
+          encoder.encode(
+            JSON.stringify({
+              type: 'init',
+              data: 'Stream connected',
+            }) + '\n',
+          ),
+        );
+
+        signal.addEventListener('abort', () => {
+          emitter.removeAllListeners();
+
+          try {
+            controller.close();
+          } catch (error) {}
+        });
+
+        emitter.on('data', (data: string) => {
+          if (signal.aborted) return;
+
           try {
             const parsedData = JSON.parse(data);
+
             if (parsedData.type === 'response') {
-              message += parsedData.data;
+              controller.enqueue(
+                encoder.encode(
+                  JSON.stringify({
+                    type: 'response',
+                    data: parsedData.data,
+                  }) + '\n',
+                ),
+              );
             } else if (parsedData.type === 'sources') {
               sources = parsedData.data;
+              controller.enqueue(
+                encoder.encode(
+                  JSON.stringify({
+                    type: 'sources',
+                    data: sources,
+                  }) + '\n',
+                ),
+              );
             }
           } catch (error) {
-            reject(
-              Response.json({ message: 'Error parsing data' }, { status: 500 }),
-            );
+            controller.error(error);
           }
         });
 
         emitter.on('end', () => {
-          resolve(Response.json({ message, sources }, { status: 200 }));
+          if (signal.aborted) return;
+
+          controller.enqueue(
+            encoder.encode(
+              JSON.stringify({
+                type: 'done',
+              }) + '\n',
+            ),
+          );
+          controller.close();
         });
 
-        emitter.on('error', (error) => {
-          reject(
-            Response.json({ message: 'Search error', error }, { status: 500 }),
-          );
+        emitter.on('error', (error: any) => {
+          if (signal.aborted) return;
+
+          controller.error(error);
         });
       },
-    );
+      cancel() {
+        abortController.abort();
+      },
+    });
+
+    return new Response(stream, {
+      headers: {
+        'Content-Type': 'text/event-stream',
+        'Cache-Control': 'no-cache, no-transform',
+        Connection: 'keep-alive',
+      },
+    });
   } catch (err: any) {
     console.error(`Error in getting search results: ${err.message}`);
     return Response.json(

src/app/api/suggestions/route.ts

@@ -72,9 +72,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ suggestions }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while generating suggestions: ${err}`);
+    console.error(`An error occurred while generating suggestions: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while generating suggestions' },
+      { message: 'An error occurred while generating suggestions' },
       { status: 500 },
     );
   }

src/app/api/videos/route.ts

@@ -74,9 +74,9 @@ export const POST = async (req: Request) => {
 
     return Response.json({ videos }, { status: 200 });
   } catch (err) {
-    console.error(`An error ocurred while searching videos: ${err}`);
+    console.error(`An error occurred while searching videos: ${err}`);
     return Response.json(
-      { message: 'An error ocurred while searching videos' },
+      { message: 'An error occurred while searching videos' },
       { status: 500 },
     );
   }

src/lib/providers/anthropic.ts

@@ -1,4 +1,4 @@
-import { ChatOpenAI } from '@langchain/openai';
+import { ChatAnthropic } from '@langchain/anthropic';
 import { ChatModel } from '.';
 import { getAnthropicApiKey } from '../config';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
@@ -45,13 +45,10 @@ export const loadAnthropicChatModels = async () => {
     anthropicChatModels.forEach((model) => {
       chatModels[model.key] = {
         displayName: model.displayName,
-        model: new ChatOpenAI({
-          openAIApiKey: anthropicApiKey,
+        model: new ChatAnthropic({
+          apiKey: anthropicApiKey,
           modelName: model.key,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://api.anthropic.com/v1/',
-          },
         }) as unknown as BaseChatModel,
       };
     });

src/lib/providers/gemini.ts

@@ -1,10 +1,17 @@
-import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
+import {
+  ChatGoogleGenerativeAI,
+  GoogleGenerativeAIEmbeddings,
+} from '@langchain/google-genai';
 import { getGeminiApiKey } from '../config';
 import { ChatModel, EmbeddingModel } from '.';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { Embeddings } from '@langchain/core/embeddings';
 
 const geminiChatModels: Record<string, string>[] = [
+  {
+    displayName: 'Gemini 2.5 Pro Experimental',
+    key: 'gemini-2.5-pro-exp-03-25',
+  },
   {
     displayName: 'Gemini 2.0 Flash',
     key: 'gemini-2.0-flash',
@@ -14,8 +21,8 @@ const geminiChatModels: Record<string, string>[] = [
     key: 'gemini-2.0-flash-lite',
   },
   {
-    displayName: 'Gemini 2.0 Pro Experimental',
-    key: 'gemini-2.0-pro-exp-02-05',
+    displayName: 'Gemini 2.0 Flash Thinking Experimental',
+    key: 'gemini-2.0-flash-thinking-exp-01-21',
   },
   {
     displayName: 'Gemini 1.5 Flash',
@@ -49,13 +56,10 @@ export const loadGeminiChatModels = async () => {
     geminiChatModels.forEach((model) => {
       chatModels[model.key] = {
         displayName: model.displayName,
-        model: new ChatOpenAI({
-          openAIApiKey: geminiApiKey,
+        model: new ChatGoogleGenerativeAI({
+          apiKey: geminiApiKey,
           modelName: model.key,
           temperature: 0.7,
-          configuration: {
-            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
-          },
         }) as unknown as BaseChatModel,
       };
     });
@@ -78,12 +82,9 @@ export const loadGeminiEmbeddingModels = async () => {
     geminiEmbeddingModels.forEach((model) => {
       embeddingModels[model.key] = {
         displayName: model.displayName,
-        model: new OpenAIEmbeddings({
-          openAIApiKey: geminiApiKey,
+        model: new GoogleGenerativeAIEmbeddings({
+          apiKey: geminiApiKey,
           modelName: model.key,
-          configuration: {
-            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
-          },
         }) as unknown as Embeddings,
       };
     });

src/lib/search/metaSearchAgent.ts

@@ -6,6 +6,11 @@ import {
   MessagesPlaceholder,
   PromptTemplate,
 } from '@langchain/core/prompts';
+import {
+  RunnableLambda,
+  RunnableMap,
+  RunnableSequence,
+} from '@langchain/core/runnables';
 import { BaseMessage } from '@langchain/core/messages';
 import { StringOutputParser } from '@langchain/core/output_parsers';
 import LineListOutputParser from '../outputParsers/listLineOutputParser';
@@ -19,7 +24,6 @@ import computeSimilarity from '../utils/computeSimilarity';
 import formatChatHistoryAsString from '../utils/formatHistory';
 import eventEmitter from 'events';
 import { StreamEvent } from '@langchain/core/tracers/log_stream';
-import { EventEmitter } from 'node:stream';
 
 export interface MetaSearchAgentType {
   searchAndAnswer: (
@@ -42,7 +46,7 @@ interface Config {
   activeEngines: string[];
 }
 
-type SearchInput = {
+type BasicChainInput = {
   chat_history: BaseMessage[];
   query: string;
 };
@@ -55,240 +59,235 @@ class MetaSearchAgent implements MetaSearchAgentType {
     this.config = config;
   }
 
-  private async searchSources(
-    llm: BaseChatModel,
-    input: SearchInput,
-    emitter: EventEmitter,
-  ) {
+  private async createSearchRetrieverChain(llm: BaseChatModel) {
     (llm as unknown as ChatOpenAI).temperature = 0;
 
-    const chatPrompt = PromptTemplate.fromTemplate(
-      this.config.queryGeneratorPrompt,
-    );
+    return RunnableSequence.from([
+      PromptTemplate.fromTemplate(this.config.queryGeneratorPrompt),
+      llm,
+      this.strParser,
+      RunnableLambda.from(async (input: string) => {
+        const linksOutputParser = new LineListOutputParser({
+          key: 'links',
+        });
 
-    const processedChatPrompt = await chatPrompt.invoke({
-      chat_history: formatChatHistoryAsString(input.chat_history),
-      query: input.query,
-    });
+        const questionOutputParser = new LineOutputParser({
+          key: 'question',
+        });
 
-    const llmRes = await llm.invoke(processedChatPrompt);
-    const messageStr = await this.strParser.invoke(llmRes);
+        const links = await linksOutputParser.parse(input);
+        let question = this.config.summarizer
+          ? await questionOutputParser.parse(input)
+          : input;
 
-    const linksOutputParser = new LineListOutputParser({
-      key: 'links',
-    });
-
-    const questionOutputParser = new LineOutputParser({
-      key: 'question',
-    });
-
-    const links = await linksOutputParser.parse(messageStr);
-    let question = this.config.summarizer
-      ? await questionOutputParser.parse(messageStr)
-      : messageStr;
-
-    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,
-            },
-          });
+        if (question === 'not_needed') {
+          return { query: '', docs: [] };
         }
 
-        const docIndex = docGroups.findIndex(
-          (d) =>
-            d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
-        );
+        if (links.length > 0) {
+          if (question.length === 0) {
+            question = 'summarize';
+          }
 
-        if (docIndex !== -1) {
-          docGroups[docIndex].pageContent =
-            docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
-          docGroups[docIndex].metadata.totalDocs += 1;
-        }
-      });
+          let docs: Document[] = [];
 
-      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.
+          const linkDocs = await getDocumentsFromLinks({ links });
 
-        The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
+          const docGroups: Document[] = [];
 
-        <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>
+          linkDocs.map((doc) => {
+            const URLDocExists = docGroups.find(
+              (d) =>
+                d.metadata.url === doc.metadata.url &&
+                d.metadata.totalDocs < 10,
+            );
 
-        <query>
-        What is Docker and how does it work?
-        </query>
+            if (!URLDocExists) {
+              docGroups.push({
+                ...doc,
+                metadata: {
+                  ...doc.metadata,
+                  totalDocs: 1,
+                },
+              });
+            }
 
-        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>
+            const docIndex = docGroups.findIndex(
+              (d) =>
+                d.metadata.url === doc.metadata.url &&
+                d.metadata.totalDocs < 10,
+            );
 
-        <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,
-            },
+            if (docIndex !== -1) {
+              docGroups[docIndex].pageContent =
+                docGroups[docIndex].pageContent + `\n\n` + doc.pageContent;
+              docGroups[docIndex].metadata.totalDocs += 1;
+            }
           });
 
-          docs.push(document);
-        }),
-      );
+          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.
 
-      return { query: question, docs: docs };
-    } else {
-      question = question.replace(/<think>.*?<\/think>/g, '');
+            The text will be shared inside the \`text\` XML tag, and the query inside the \`query\` XML tag.
 
-      const res = await searchSearxng(question, {
-        language: 'en',
-        engines: this.config.activeEngines,
-      });
+            <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>
 
-      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 }),
-            },
-          }),
-      );
+            <query>
+            What is Docker and how does it work?
+            </query>
 
-      return { query: question, docs: documents };
-    }
+            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 streamAnswer(
+  private async createAnsweringChain(
     llm: BaseChatModel,
     fileIds: string[],
     embeddings: Embeddings,
     optimizationMode: 'speed' | 'balanced' | 'quality',
-    input: SearchInput,
-    emitter: EventEmitter,
   ) {
-    const chatPrompt = ChatPromptTemplate.fromMessages([
-      ['system', this.config.responsePrompt],
-      new MessagesPlaceholder('chat_history'),
-      ['user', '{query}'],
-    ]);
+    return RunnableSequence.from([
+      RunnableMap.from({
+        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;
+          let docs: Document[] | null = null;
+          let query = input.query;
 
-    if (this.config.searchWeb) {
-      const searchResults = await this.searchSources(llm, input, emitter);
+          if (this.config.searchWeb) {
+            const searchRetrieverChain =
+              await this.createSearchRetrieverChain(llm);
 
-      query = searchResults.query;
-      docs = searchResults.docs;
-    }
+            const searchRetrieverResult = await searchRetrieverChain.invoke({
+              chat_history: processedHistory,
+              query,
+            });
 
-    const sortedDocs = await this.rerankDocs(
-      query,
-      docs ?? [],
-      fileIds,
-      embeddings,
-      optimizationMode,
-    );
+            query = searchRetrieverResult.query;
+            docs = searchRetrieverResult.docs;
+          }
 
-    emitter.emit('data', JSON.stringify({ type: 'sources', data: sortedDocs }));
+          const sortedDocs = await this.rerankDocs(
+            query,
+            docs ?? [],
+            fileIds,
+            embeddings,
+            optimizationMode,
+          );
 
-    const context = this.processDocs(sortedDocs);
-
-    const formattedChatPrompt = await chatPrompt.invoke({
-      query: input.query,
-      chat_history: input.chat_history,
-      date: new Date().toISOString(),
-      context: context,
+          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',
     });
-
-    const llmRes = await llm.stream(formattedChatPrompt);
-
-    for await (const data of llmRes) {
-      const messageStr = await this.strParser.invoke(data);
-
-      emitter.emit(
-        'data',
-        JSON.stringify({ type: 'response', data: messageStr }),
-      );
-    }
-
-    emitter.emit('end');
   }
 
   private async rerankDocs(
@@ -429,6 +428,39 @@ class MetaSearchAgent implements MetaSearchAgentType {
       .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[],
@@ -439,18 +471,25 @@ class MetaSearchAgent implements MetaSearchAgentType {
   ) {
     const emitter = new eventEmitter();
 
-    this.streamAnswer(
+    const answeringChain = await this.createAnsweringChain(
       llm,
       fileIds,
       embeddings,
       optimizationMode,
+    );
+
+    const stream = answeringChain.streamEvents(
       {
         chat_history: history,
         query: message,
       },
-      emitter,
+      {
+        version: 'v1',
+      },
     );
 
+    this.handleStream(stream, emitter);
+
     return emitter;
   }
 }

yarn.lock

@@ -12,6 +12,19 @@
   resolved "https://registry.yarnpkg.com/@alloc/quick-lru/-/quick-lru-5.2.0.tgz#7bf68b20c0a350f936915fcae06f58e32007ce30"
   integrity sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==
 
+"@anthropic-ai/sdk@^0.37.0":
+  version "0.37.0"
+  resolved "https://registry.yarnpkg.com/@anthropic-ai/sdk/-/sdk-0.37.0.tgz#0018127404ecb9b8a12968068e0c4b3e8bbd6386"
+  integrity sha512-tHjX2YbkUBwEgg0JZU3EFSSAQPoK4qQR/NFYa8Vtzd5UAyXzZksCw2In69Rml4R/TyHPBfRYaLK35XiOe33pjw==
+  dependencies:
+    "@types/node" "^18.11.18"
+    "@types/node-fetch" "^2.6.4"
+    abort-controller "^3.0.0"
+    agentkeepalive "^4.2.1"
+    form-data-encoder "1.7.2"
+    formdata-node "^4.3.2"
+    node-fetch "^2.6.7"
+
 "@anthropic-ai/sdk@^0.9.1":
   version "0.9.1"
   resolved "https://registry.yarnpkg.com/@anthropic-ai/sdk/-/sdk-0.9.1.tgz#b2d2b7bf05c90dce502c9a2e869066870f69ba88"
@@ -374,6 +387,11 @@
   resolved "https://registry.yarnpkg.com/@floating-ui/utils/-/utils-0.2.8.tgz#21a907684723bbbaa5f0974cf7730bd797eb8e62"
   integrity sha512-kym7SodPp8/wloecOpcmSnWJsK7M0E5Wg8UcFA+uO4B9s5d0ywXOEro/8HM9x0rW+TljRzul/14UYz3TleT3ig==
 
+"@google/generative-ai@^0.24.0":
+  version "0.24.0"
+  resolved "https://registry.yarnpkg.com/@google/generative-ai/-/generative-ai-0.24.0.tgz#4d27af7d944c924a27a593c17ad1336535d53846"
+  integrity sha512-fnEITCGEB7NdX0BhoYZ/cq/7WPZ1QS5IzJJfC3Tg/OwkvBetMiVJciyaan297OvE4B9Jg1xvo0zIazX/9sGu1Q==
+
 "@headlessui/react@^2.2.0":
   version "2.2.0"
   resolved "https://registry.yarnpkg.com/@headlessui/react/-/react-2.2.0.tgz#a8e32f0899862849a1ce1615fa280e7891431ab7"
@@ -575,6 +593,16 @@
     "@jridgewell/resolve-uri" "^3.1.0"
     "@jridgewell/sourcemap-codec" "^1.4.14"
 
+"@langchain/anthropic@^0.3.15":
+  version "0.3.15"
+  resolved "https://registry.yarnpkg.com/@langchain/anthropic/-/anthropic-0.3.15.tgz#0244cdb345cb492eb40aedd681881ebadfbb73f2"
+  integrity sha512-Ar2viYcZ64idgV7EtCBCb36tIkNtPAhQRxSaMTWPHGspFgMfvwRoleVri9e90sCpjpS9xhlHsIQ0LlUS/Atsrw==
+  dependencies:
+    "@anthropic-ai/sdk" "^0.37.0"
+    fast-xml-parser "^4.4.1"
+    zod "^3.22.4"
+    zod-to-json-schema "^3.22.4"
+
 "@langchain/community@^0.3.36":
   version "0.3.36"
   resolved "https://registry.yarnpkg.com/@langchain/community/-/community-0.3.36.tgz#e4c13b8f928b17e0f9257395f43be2246dfada40"
@@ -640,6 +668,14 @@
     zod "^3.22.4"
     zod-to-json-schema "^3.22.3"
 
+"@langchain/google-genai@^0.1.12":
+  version "0.1.12"
+  resolved "https://registry.yarnpkg.com/@langchain/google-genai/-/google-genai-0.1.12.tgz#6727253bda6f0d87cd74cf0bb6b1e0f398f60f32"
+  integrity sha512-0Ea0E2g63ejCuormVxbuoyJQ5BYN53i2/fb6WP8bMKzyh+y43R13V8JqOtr3e/GmgNyv3ou/VeaZjx7KAvu/0g==
+  dependencies:
+    "@google/generative-ai" "^0.24.0"
+    zod-to-json-schema "^3.22.4"
+
 "@langchain/openai@>=0.1.0 <0.5.0", "@langchain/openai@>=0.2.0 <0.5.0":
   version "0.4.5"
   resolved "https://registry.yarnpkg.com/@langchain/openai/-/openai-0.4.5.tgz#d18e207c3ec3f2ecaa4698a5a5888092f643da52"
@@ -2369,6 +2405,13 @@ fast-levenshtein@^2.0.6:
   resolved "https://registry.yarnpkg.com/fast-levenshtein/-/fast-levenshtein-2.0.6.tgz#3d8a5c66883a16a30ca8643e851f19baa7797917"
   integrity sha512-DCXu6Ifhqcks7TZKY3Hxp3y6qphY5SJZmrWMDrKcERSOXWQdMhU9Ig/PYrzyw/ul9jOIyh0N4M0tbC5hodg8dw==
 
+fast-xml-parser@^4.4.1:
+  version "4.5.3"
+  resolved "https://registry.yarnpkg.com/fast-xml-parser/-/fast-xml-parser-4.5.3.tgz#c54d6b35aa0f23dc1ea60b6c884340c006dc6efb"
+  integrity sha512-RKihhV+SHsIUGXObeVy9AXiBbFwkVk7Syp8XgwN5U3JV416+Gwp/GO9i0JYKmikykgz/UHRrrV4ROuZEo/T0ig==
+  dependencies:
+    strnum "^1.1.1"
+
 fastq@^1.6.0:
   version "1.17.1"
   resolved "https://registry.yarnpkg.com/fastq/-/fastq-1.17.1.tgz#2a523f07a4e7b1e81a42b91b8bf2254107753b47"
@@ -4458,6 +4501,11 @@ 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==
 
+strnum@^1.1.1:
+  version "1.1.2"
+  resolved "https://registry.yarnpkg.com/strnum/-/strnum-1.1.2.tgz#57bca4fbaa6f271081715dbc9ed7cee5493e28e4"
+  integrity sha512-vrN+B7DBIoTTZjnPNewwhx6cBA/H+IS7rfW68n7XxC1y7uoiGQBxaKzqucGUgavX15dJgiGztLJ8vxuEzwqBdA==
+
 styled-jsx@5.1.6:
   version "5.1.6"
   resolved "https://registry.yarnpkg.com/styled-jsx/-/styled-jsx-5.1.6.tgz#83b90c077e6c6a80f7f5e8781d0f311b2fe41499"
@@ -4955,6 +5003,11 @@ zod-to-json-schema@^3.22.3, zod-to-json-schema@^3.22.5:
   resolved "https://registry.yarnpkg.com/zod-to-json-schema/-/zod-to-json-schema-3.22.5.tgz#3646e81cfc318dbad2a22519e5ce661615418673"
   integrity sha512-+akaPo6a0zpVCCseDed504KBJUQpEW5QZw7RMneNmKw+fGaML1Z9tUNLnHHAC8x6dzVRO1eB2oEMyZRnuBZg7Q==
 
+zod-to-json-schema@^3.22.4:
+  version "3.24.5"
+  resolved "https://registry.yarnpkg.com/zod-to-json-schema/-/zod-to-json-schema-3.24.5.tgz#d1095440b147fb7c2093812a53c54df8d5df50a3"
+  integrity sha512-/AuWwMP+YqiPbsJx5D6TfgRTc4kTLjsh5SOcd4bLsfUg2RcEXrFMJl1DGgdHy2aCfsIA/cr/1JM0xcB2GZji8g==
+
 zod@^3.22.3, zod@^3.22.4:
   version "3.22.4"
   resolved "https://registry.yarnpkg.com/zod/-/zod-3.22.4.tgz#f31c3a9386f61b1f228af56faa9255e845cf3fff"