feat(video-search): add video search

src/agents/videoSearchAgent.ts

@@ -0,0 +1,90 @@
+import {
+  RunnableSequence,
+  RunnableMap,
+  RunnableLambda,
+} from '@langchain/core/runnables';
+import { PromptTemplate } from '@langchain/core/prompts';
+import formatChatHistoryAsString from '../utils/formatHistory';
+import { BaseMessage } 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';
+
+const VideoSearchChainPrompt = `
+  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.
+  
+  Example:
+  1. Follow up question: How does a car work?
+  Rephrased: How does a car work?
+  
+  2. Follow up question: What is the theory of relativity?
+  Rephrased: What is theory of relativity
+  
+  3. Follow up question: How does an AC work?
+  Rephrased: How does an AC work
+  
+  Conversation:
+  {chat_history}
+  
+  Follow up question: {query}
+  Rephrased question:
+  `;
+
+type VideoSearchChainInput = {
+  chat_history: BaseMessage[];
+  query: string;
+};
+
+const strParser = new StringOutputParser();
+
+const createVideoSearchChain = (llm: BaseChatModel) => {
+  return RunnableSequence.from([
+    RunnableMap.from({
+      chat_history: (input: VideoSearchChainInput) => {
+        return formatChatHistoryAsString(input.chat_history);
+      },
+      query: (input: VideoSearchChainInput) => {
+        return input.query;
+      },
+    }),
+    PromptTemplate.fromTemplate(VideoSearchChainPrompt),
+    llm,
+    strParser,
+    RunnableLambda.from(async (input: string) => {
+      const res = await searchSearxng(input, {
+        engines: ['youtube'],
+      });
+
+      const videos = [];
+
+      res.results.forEach((result) => {
+        if (
+          result.thumbnail &&
+          result.url &&
+          result.title &&
+          result.iframe_src
+        ) {
+          videos.push({
+            img_src: result.thumbnail,
+            url: result.url,
+            title: result.title,
+            iframe_src: result.iframe_src,
+          });
+        }
+      });
+
+      return videos.slice(0, 10);
+    }),
+  ]);
+};
+
+const handleVideoSearch = (
+  input: VideoSearchChainInput,
+  llm: BaseChatModel,
+) => {
+  const VideoSearchChain = createVideoSearchChain(llm);
+  return VideoSearchChain.invoke(input);
+};
+
+export default handleVideoSearch;

src/lib/searxng.ts

@@ -13,8 +13,10 @@ interface SearxngSearchResult {
   url: string;
   img_src?: string;
   thumbnail_src?: string;
+  thumbnail?: string;
   content?: string;
   author?: string;
+  iframe_src?: string;
 }
 
 export const searchSearxng = async (

src/routes/index.ts

@@ -1,10 +1,12 @@
 import express from 'express';
 import imagesRouter from './images';
+import videosRouter from './videos';
 import configRouter from './config';
 
 const router = express.Router();
 
 router.use('/images', imagesRouter);
+router.use('/videos', videosRouter);
 router.use('/config', configRouter);
 
 export default router;

src/routes/videos.ts

@@ -0,0 +1,47 @@
+import express from 'express';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { getAvailableProviders } from '../lib/providers';
+import { getChatModel, getChatModelProvider } from '../config';
+import { HumanMessage, AIMessage } from '@langchain/core/messages';
+import logger from '../utils/logger';
+import handleVideoSearch from '../agents/videoSearchAgent';
+
+const router = express.Router();
+
+router.post('/', async (req, res) => {
+  try {
+    let { query, chat_history } = req.body;
+
+    chat_history = chat_history.map((msg: any) => {
+      if (msg.role === 'user') {
+        return new HumanMessage(msg.content);
+      } else if (msg.role === 'assistant') {
+        return new AIMessage(msg.content);
+      }
+    });
+
+    const models = await getAvailableProviders();
+    const provider = getChatModelProvider();
+    const chatModel = getChatModel();
+
+    let llm: BaseChatModel | undefined;
+
+    if (models[provider] && models[provider][chatModel]) {
+      llm = models[provider][chatModel] as BaseChatModel | undefined;
+    }
+
+    if (!llm) {
+      res.status(500).json({ message: 'Invalid LLM model selected' });
+      return;
+    }
+
+    const videos = await handleVideoSearch({ chat_history, query }, llm);
+
+    res.status(200).json({ videos });
+  } catch (err) {
+    res.status(500).json({ message: 'An error has occurred.' });
+    logger.error(`Error in video search: ${err.message}`);
+  }
+});
+
+export default router;