Merge branch 'ItzCrazyKns:master' into master

package.json

@@ -6,7 +6,7 @@
   "scripts": {
     "start": "node dist/app.js",
     "build": "tsc",
-    "dev": "nodemon src/app.ts" , 
+    "dev": "nodemon src/app.ts",
     "format": "prettier . --check",
     "format:write": "prettier . --write"
   },

src/agents/suggestionGeneratorAgent.ts

@@ -0,0 +1,55 @@
+import { RunnableSequence, RunnableMap } from '@langchain/core/runnables';
+import ListLineOutputParser from '../lib/outputParsers/listLineOutputParser';
+import { PromptTemplate } from '@langchain/core/prompts';
+import formatChatHistoryAsString from '../utils/formatHistory';
+import { BaseMessage } from '@langchain/core/messages';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { ChatOpenAI } from '@langchain/openai';
+
+const suggestionGeneratorPrompt = `
+You are an AI suggestion generator for an AI powered search engine. You will be given a conversation below. You need to generate 4-5 suggestions based on the conversation. The suggestion should be relevant to the conversation that can be used by the user to ask the chat model for more information.
+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>
+Suggestion 1
+Suggestion 2
+Suggestion 3
+</suggestions>
+
+Conversation:
+{chat_history}
+`;
+
+type SuggestionGeneratorInput = {
+  chat_history: BaseMessage[];
+};
+
+const outputParser = new ListLineOutputParser({
+  key: 'suggestions',
+});
+
+const createSuggestionGeneratorChain = (llm: BaseChatModel) => {
+  return RunnableSequence.from([
+    RunnableMap.from({
+      chat_history: (input: SuggestionGeneratorInput) =>
+        formatChatHistoryAsString(input.chat_history),
+    }),
+    PromptTemplate.fromTemplate(suggestionGeneratorPrompt),
+    llm,
+    outputParser,
+  ]);
+};
+
+const generateSuggestions = (
+  input: SuggestionGeneratorInput,
+  llm: BaseChatModel,
+) => {
+  (llm as ChatOpenAI).temperature = 0;
+  const suggestionGeneratorChain = createSuggestionGeneratorChain(llm);
+  return suggestionGeneratorChain.invoke(input);
+};
+
+export default generateSuggestions;

src/lib/outputParsers/listLineOutputParser.ts

@@ -0,0 +1,43 @@
+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[]> {
+    const regex = /^(\s*(-|\*|\d+\.\s|\d+\)\s|\u2022)\s*)+/;
+    const startKeyIndex = text.indexOf(`<${this.key}>`);
+    const endKeyIndex = text.indexOf(`</${this.key}>`);
+    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/providers.ts

@@ -157,7 +157,6 @@ export const getAvailableEmbeddingModelProviders = async () => {
         });
         return acc;
       }, {});
-
     } catch (err) {
       logger.error(`Error loading Ollama embeddings: ${err}`);
     }
@@ -172,10 +171,10 @@ export const getAvailableEmbeddingModelProviders = async () => {
         modelName: 'Xenova/gte-small',
       }),
       'Bert Multilingual': new HuggingFaceTransformersEmbeddings({
-        modelName: 'Xenova/bert-base-multilingual-uncased'
+        modelName: 'Xenova/bert-base-multilingual-uncased',
       }),
     };
-  } catch(err) {
+  } catch (err) {
     logger.error(`Error loading local embeddings: ${err}`);
   }
 

src/routes/index.ts

@@ -3,6 +3,7 @@ import imagesRouter from './images';
 import videosRouter from './videos';
 import configRouter from './config';
 import modelsRouter from './models';
+import suggestionsRouter from './suggestions';
 
 const router = express.Router();
 
@@ -10,5 +11,6 @@ router.use('/images', imagesRouter);
 router.use('/videos', videosRouter);
 router.use('/config', configRouter);
 router.use('/models', modelsRouter);
+router.use('/suggestions', suggestionsRouter);
 
 export default router;

src/routes/suggestions.ts

@@ -0,0 +1,46 @@
+import express from 'express';
+import generateSuggestions from '../agents/suggestionGeneratorAgent';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { getAvailableChatModelProviders } from '../lib/providers';
+import { HumanMessage, AIMessage } from '@langchain/core/messages';
+import logger from '../utils/logger';
+
+const router = express.Router();
+
+router.post('/', async (req, res) => {
+  try {
+    let { chat_history, chat_model, chat_model_provider } = 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 chatModels = await getAvailableChatModelProviders();
+    const provider = chat_model_provider || Object.keys(chatModels)[0];
+    const chatModel = chat_model || Object.keys(chatModels[provider])[0];
+
+    let llm: BaseChatModel | undefined;
+
+    if (chatModels[provider] && chatModels[provider][chatModel]) {
+      llm = chatModels[provider][chatModel] as BaseChatModel | undefined;
+    }
+
+    if (!llm) {
+      res.status(500).json({ message: 'Invalid LLM model selected' });
+      return;
+    }
+
+    const suggestions = await generateSuggestions({ chat_history }, llm);
+
+    res.status(200).json({ suggestions: suggestions });
+  } catch (err) {
+    res.status(500).json({ message: 'An error has occurred.' });
+    logger.error(`Error in generating suggestions: ${err.message}`);
+  }
+});
+
+export default router;