feat(metaSearchAgent): eliminate runnables

2025-06-20 08:48:35 +00:00 · 2025-03-24 17:27:54 +05:30
14 changed files with 268 additions and 484 deletions
--- a/docs/API/SEARCH.md
+++ b/docs/API/SEARCH.md
@ -32,8 +32,7 @@ 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
+  ]
 }
 ```

@ -72,13 +71,11 @@ 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.

-#### Standard Response (stream: false)
+#### Example Response

 ```json
 {
@ -103,28 +100,6 @@ 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.
--- a/package.json
+++ b/package.json
@ -1,6 +1,6 @@
 {
  "name": "perplexica-frontend",
-  "version": "1.10.1",
+  "version": "1.10.0",
  "license": "MIT",
  "author": "ItzCrazyKns",
  "scripts": {
@ -15,10 +15,8 @@
    "@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",
--- a/src/app/api/chat/route.ts
+++ b/src/app/api/chat/route.ts
@ -295,9 +295,9 @@ export const POST = async (req: Request) => {
      },
    });
  } catch (err) {
-    console.error('An error occurred while processing chat request:', err);
+    console.error('An error ocurred while processing chat request:', err);
    return Response.json(
-      { message: 'An error occurred while processing chat request' },
+      { message: 'An error ocurred while processing chat request' },
      { status: 500 },
    );
  }
--- a/src/app/api/config/route.ts
+++ b/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 occurred while getting config:', err);
+    console.error('An error ocurred while getting config:', err);
    return Response.json(
-      { message: 'An error occurred while getting config' },
+      { message: 'An error ocurred 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 occurred while updating config:', err);
+    console.error('An error ocurred while updating config:', err);
    return Response.json(
-      { message: 'An error occurred while updating config' },
+      { message: 'An error ocurred while updating config' },
      { status: 500 },
    );
  }
--- a/src/app/api/discover/route.ts
+++ b/src/app/api/discover/route.ts
@ -48,7 +48,7 @@ export const GET = async (req: Request) => {
      },
    );
  } catch (err) {
-    console.error(`An error occurred in discover route: ${err}`);
+    console.error(`An error ocurred in discover route: ${err}`);
    return Response.json(
      {
        message: 'An error has occurred',
--- a/src/app/api/images/route.ts
+++ b/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 occurred while searching images: ${err}`);
+    console.error(`An error ocurred while searching images: ${err}`);
    return Response.json(
-      { message: 'An error occurred while searching images' },
+      { message: 'An error ocurred while searching images' },
      { status: 500 },
    );
  }
--- a/src/app/api/models/route.ts
+++ b/src/app/api/models/route.ts
@ -34,7 +34,7 @@ export const GET = async (req: Request) => {
      },
    );
  } catch (err) {
-    console.error('An error occurred while fetching models', err);
+    console.error('An error ocurred while fetching models', err);
    return Response.json(
      {
        message: 'An error has occurred.',
--- a/src/app/api/search/route.ts
+++ b/src/app/api/search/route.ts
@ -33,7 +33,6 @@ interface ChatRequestBody {
  embeddingModel?: embeddingModel;
  query: string;
  history: Array<[string, string]>;
-  stream?: boolean;
 }

 export const POST = async (req: Request) => {
@ -49,7 +48,6 @@ 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'
@ -127,137 +125,40 @@ export const POST = async (req: Request) => {
      [],
    );

-    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) {
+    return new Promise(
+      (
+        resolve: (value: Response) => void,
+        reject: (value: Response) => void,
+      ) => {
+        let message = '';
        let sources: any[] = [];

-        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;
-
+        emitter.on('data', (data) => {
          try {
            const parsedData = JSON.parse(data);
-
            if (parsedData.type === 'response') {
-              controller.enqueue(
-                encoder.encode(
-                  JSON.stringify({
-                    type: 'response',
-                    data: parsedData.data,
-                  }) + '\n',
-                ),
-              );
+              message += parsedData.data;
            } else if (parsedData.type === 'sources') {
              sources = parsedData.data;
-              controller.enqueue(
-                encoder.encode(
-                  JSON.stringify({
-                    type: 'sources',
-                    data: sources,
-                  }) + '\n',
-                ),
-              );
            }
          } catch (error) {
-            controller.error(error);
+            reject(
+              Response.json({ message: 'Error parsing data' }, { status: 500 }),
+            );
          }
        });

        emitter.on('end', () => {
-          if (signal.aborted) return;
+          resolve(Response.json({ message, sources }, { status: 200 }));
+        });

-          controller.enqueue(
-            encoder.encode(
-              JSON.stringify({
-                type: 'done',
-              }) + '\n',
-            ),
+        emitter.on('error', (error) => {
+          reject(
+            Response.json({ message: 'Search error', error }, { status: 500 }),
          );
-          controller.close();
-        });
-
-        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(
--- a/src/app/api/suggestions/route.ts
+++ b/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 occurred while generating suggestions: ${err}`);
+    console.error(`An error ocurred while generating suggestions: ${err}`);
    return Response.json(
-      { message: 'An error occurred while generating suggestions' },
+      { message: 'An error ocurred while generating suggestions' },
      { status: 500 },
    );
  }
--- a/src/app/api/videos/route.ts
+++ b/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 occurred while searching videos: ${err}`);
+    console.error(`An error ocurred while searching videos: ${err}`);
    return Response.json(
-      { message: 'An error occurred while searching videos' },
+      { message: 'An error ocurred while searching videos' },
      { status: 500 },
    );
  }
--- a/src/lib/providers/anthropic.ts
+++ b/src/lib/providers/anthropic.ts
@ -1,4 +1,4 @@
-import { ChatAnthropic } from '@langchain/anthropic';
+import { ChatOpenAI } from '@langchain/openai';
 import { ChatModel } from '.';
 import { getAnthropicApiKey } from '../config';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
@ -45,10 +45,13 @@ export const loadAnthropicChatModels = async () => {
    anthropicChatModels.forEach((model) => {
      chatModels[model.key] = {
        displayName: model.displayName,
-        model: new ChatAnthropic({
-          apiKey: anthropicApiKey,
+        model: new ChatOpenAI({
+          openAIApiKey: anthropicApiKey,
          modelName: model.key,
          temperature: 0.7,
+          configuration: {
+            baseURL: 'https://api.anthropic.com/v1/',
+          },
        }) as unknown as BaseChatModel,
      };
    });
--- a/src/lib/providers/gemini.ts
+++ b/src/lib/providers/gemini.ts
@ -1,17 +1,10 @@
-import {
-  ChatGoogleGenerativeAI,
-  GoogleGenerativeAIEmbeddings,
-} from '@langchain/google-genai';
+import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
 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',
@ -21,8 +14,8 @@ const geminiChatModels: Record<string, string>[] = [
    key: 'gemini-2.0-flash-lite',
  },
  {
-    displayName: 'Gemini 2.0 Flash Thinking Experimental',
-    key: 'gemini-2.0-flash-thinking-exp-01-21',
+    displayName: 'Gemini 2.0 Pro Experimental',
+    key: 'gemini-2.0-pro-exp-02-05',
  },
  {
    displayName: 'Gemini 1.5 Flash',
@ -56,10 +49,13 @@ export const loadGeminiChatModels = async () => {
    geminiChatModels.forEach((model) => {
      chatModels[model.key] = {
        displayName: model.displayName,
-        model: new ChatGoogleGenerativeAI({
-          apiKey: geminiApiKey,
+        model: new ChatOpenAI({
+          openAIApiKey: geminiApiKey,
          modelName: model.key,
          temperature: 0.7,
+          configuration: {
+            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
+          },
        }) as unknown as BaseChatModel,
      };
    });
@ -82,9 +78,12 @@ export const loadGeminiEmbeddingModels = async () => {
    geminiEmbeddingModels.forEach((model) => {
      embeddingModels[model.key] = {
        displayName: model.displayName,
-        model: new GoogleGenerativeAIEmbeddings({
-          apiKey: geminiApiKey,
+        model: new OpenAIEmbeddings({
+          openAIApiKey: geminiApiKey,
          modelName: model.key,
+          configuration: {
+            baseURL: 'https://generativelanguage.googleapis.com/v1beta/openai/',
+          },
        }) as unknown as Embeddings,
      };
    });
--- a/src/lib/search/metaSearchAgent.ts
+++ b/src/lib/search/metaSearchAgent.ts
@ -6,11 +6,6 @@ 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';
@ -24,6 +19,7 @@ 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: (
@ -46,7 +42,7 @@ interface Config {
  activeEngines: string[];
 }

-type BasicChainInput = {
+type SearchInput = {
  chat_history: BaseMessage[];
  query: string;
 };
@ -59,235 +55,240 @@ class MetaSearchAgent implements MetaSearchAgentType {
    this.config = config;
  }

-  private async createSearchRetrieverChain(llm: BaseChatModel) {
+  private async searchSources(
+    llm: BaseChatModel,
+    input: SearchInput,
+    emitter: EventEmitter,
+  ) {
    (llm as unknown as ChatOpenAI).temperature = 0;

-    return RunnableSequence.from([
-      PromptTemplate.fromTemplate(this.config.queryGeneratorPrompt),
-      llm,
-      this.strParser,
-      RunnableLambda.from(async (input: string) => {
-        const linksOutputParser = new LineListOutputParser({
-          key: 'links',
-        });
+    const chatPrompt = PromptTemplate.fromTemplate(
+      this.config.queryGeneratorPrompt,
+    );

-        const questionOutputParser = new LineOutputParser({
-          key: 'question',
-        });
+    const processedChatPrompt = await chatPrompt.invoke({
+      chat_history: formatChatHistoryAsString(input.chat_history),
+      query: input.query,
+    });

-        const links = await linksOutputParser.parse(input);
-        let question = this.config.summarizer
-          ? await questionOutputParser.parse(input)
-          : input;
+    const llmRes = await llm.invoke(processedChatPrompt);
+    const messageStr = await this.strParser.invoke(llmRes);

-        if (question === 'not_needed') {
-          return { query: '', docs: [] };
+    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 (links.length > 0) {
-          if (question.length === 0) {
-            question = 'summarize';
-          }
+        const docIndex = docGroups.findIndex(
+          (d) =>
+            d.metadata.url === doc.metadata.url && d.metadata.totalDocs < 10,
+        );

-          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 };
+        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(
+  private async streamAnswer(
    llm: BaseChatModel,
    fileIds: string[],
    embeddings: Embeddings,
    optimizationMode: 'speed' | 'balanced' | 'quality',
+    input: SearchInput,
+    emitter: EventEmitter,
  ) {
-    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,
-          );
+    const chatPrompt = ChatPromptTemplate.fromMessages([
+      ['system', this.config.responsePrompt],
+      new MessagesPlaceholder('chat_history'),
+      ['user', '{query}'],
+    ]);

-          let docs: Document[] | null = null;
-          let query = input.query;
+    let docs: Document[] | null = null;
+    let query = input.query;

-          if (this.config.searchWeb) {
-            const searchRetrieverChain =
-              await this.createSearchRetrieverChain(llm);
+    if (this.config.searchWeb) {
+      const searchResults = await this.searchSources(llm, input, emitter);

-            const searchRetrieverResult = await searchRetrieverChain.invoke({
-              chat_history: processedHistory,
-              query,
-            });
+      query = searchResults.query;
+      docs = searchResults.docs;
+    }

-            query = searchRetrieverResult.query;
-            docs = searchRetrieverResult.docs;
-          }
+    const sortedDocs = await this.rerankDocs(
+      query,
+      docs ?? [],
+      fileIds,
+      embeddings,
+      optimizationMode,
+    );

-          const sortedDocs = await this.rerankDocs(
-            query,
-            docs ?? [],
-            fileIds,
-            embeddings,
-            optimizationMode,
-          );
+    emitter.emit('data', JSON.stringify({ type: 'sources', data: sortedDocs }));

-          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 context = this.processDocs(sortedDocs);
+
+    const formattedChatPrompt = await chatPrompt.invoke({
+      query: input.query,
+      chat_history: input.chat_history,
+      date: new Date().toISOString(),
+      context: context,
    });
+
+    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(
@ -428,39 +429,6 @@ 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[],
@ -471,25 +439,18 @@ class MetaSearchAgent implements MetaSearchAgentType {
  ) {
    const emitter = new eventEmitter();

-    const answeringChain = await this.createAnsweringChain(
+    this.streamAnswer(
      llm,
      fileIds,
      embeddings,
      optimizationMode,
-    );
-
-    const stream = answeringChain.streamEvents(
      {
        chat_history: history,
        query: message,
      },
-      {
-        version: 'v1',
-      },
+      emitter,
    );

-    this.handleStream(stream, emitter);
-
    return emitter;
  }
 }
--- a/yarn.lock
+++ b/yarn.lock
@ -12,19 +12,6 @@
  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"
@ -387,11 +374,6 @@
  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"
@ -593,16 +575,6 @@
    "@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"
@ -668,14 +640,6 @@
    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"
@ -2405,13 +2369,6 @@ 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"
@ -4501,11 +4458,6 @@ 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"
@ -5003,11 +4955,6 @@ 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"